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Wu HH, Priester A, Khoshnoodi P, Zhang Z, Shakeri S, Afshari Mirak S, Asvadi NH, Ahuja P, Sung K, Natarajan S, Sisk A, Reiter R, Raman S, Enzmann D. A system using patient-specific 3D-printed molds to spatially align in vivo MRI with ex vivo MRI and whole-mount histopathology for prostate cancer research. J Magn Reson Imaging 2018; 49:270-279. [PMID: 30069968 DOI: 10.1002/jmri.26189] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 04/25/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Patient-specific 3D-printed molds and ex vivo MRI of the resected prostate have been two important strategies to align MRI with whole-mount histopathology (WMHP) for prostate cancer (PCa) research, but the combination of these two strategies has not been systematically evaluated. PURPOSE To develop and evaluate a system that combines patient-specific 3D-printed molds with ex vivo MRI (ExV) to spatially align in vivo MRI (InV), ExV, and WMHP in PCa patients. STUDY TYPE Prospective cohort study. POPULATION Seventeen PCa patients who underwent 3T MRI and robotic-assisted laparoscopic radical prostatectomy (RALP). FIELD STRENGTH/SEQUENCES T2 -weighted turbo spin-echo sequences at 3T. ASSESSMENT Immediately after RALP, the fresh whole prostate specimens were imaged in patient-specific 3D-printed molds by 3T MRI and then sectioned to create WMHP slides. The time required for ExV was measured to assess impact on workflow. InV, ExV, and WMHP images were registered. Spatial alignment was evaluated using: slide offset (mm) between ExV slice locations and WMHP slides; overlap of the 3D prostate contour on InV versus ExV using Dice's coefficient (0 to 1); and 2D target registration error (TRE, mm) between corresponding landmarks on InV, ExV, and WMHP. Data are reported as mean ± standard deviation (SD). STATISTICAL TESTING Differences in 2D TRE before versus after registration were compared using the Wilcoxon signed-rank test (P < 0.05 considered significant). RESULTS ExV (duration 115 ± 15 min) was successfully incorporated into the workflow for all cases. Absolute slide offset was 1.58 ± 1.57 mm. Dice's coefficient was 0.865 ± 0.035. 2D TRE was significantly reduced after registration (P < 0.01) with mean (±SD of per patient means) of 1.9 ± 0.6 mm for InV versus ExV, 1.4 ± 0.5 mm for WMHP versus ExV, and 2.0 ± 0.5 mm for WMHP versus InV. DATA CONCLUSION The proposed system combines patient-specific 3D-printed molds with ExV to achieve spatial alignment between InV, ExV, and WMHP with mean 2D TRE of 1-2 mm. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:270-279.
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Affiliation(s)
- Holden H Wu
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Alan Priester
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA.,Department of Urology, University of California Los Angeles, Los Angeles, California, USA
| | - Pooria Khoshnoodi
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Zhaohuan Zhang
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Sepideh Shakeri
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Sohrab Afshari Mirak
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Nazanin H Asvadi
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Preeti Ahuja
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Kyunghyun Sung
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Shyam Natarajan
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA.,Department of Urology, University of California Los Angeles, Los Angeles, California, USA
| | - Anthony Sisk
- Department of Pathology, University of California Los Angeles, Los Angeles, California, USA
| | - Robert Reiter
- Department of Urology, University of California Los Angeles, Los Angeles, California, USA
| | - Steven Raman
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.,Department of Urology, University of California Los Angeles, Los Angeles, California, USA
| | - Dieter Enzmann
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA
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Orczyk C, Rosenkrantz AB, Mikheev A, Villers A, Bernaudin M, Taneja SS, Valable S, Rusinek H. 3D Registration of mpMRI for Assessment of Prostate Cancer Focal Therapy. Acad Radiol 2017; 24:1544-1555. [PMID: 29122471 PMCID: PMC6025844 DOI: 10.1016/j.acra.2017.06.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 05/25/2017] [Accepted: 06/09/2017] [Indexed: 01/16/2023]
Abstract
RATIONALE AND OBJECTIVES This study aimed to assess a novel method of three-dimensional (3D) co-registration of prostate magnetic resonance imaging (MRI) examinations performed before and after prostate cancer focal therapy. MATERIALS AND METHODS We developed a software platform for automatic 3D deformable co-registration of prostate MRI at different time points and applied this method to 10 patients who underwent focal ablative therapy. MRI examinations were performed preoperatively, as well as 1 week and 6 months post treatment. Rigid registration served as reference for assessing co-registration accuracy and precision. RESULTS Segmentation of preoperative and postoperative prostate revealed a significant postoperative volume decrease of the gland that averaged 6.49 cc (P = .017). Applying deformable transformation based on mutual information from 120 pairs of MRI slices, we refined by 2.9 mm (max. 6.25 mm) the alignment of the ablation zone, segmented from contrast-enhanced images on the 1-week postoperative examination, to the 6-month postoperative T2-weighted images. This represented a 500% improvement over the rigid approach (P = .001), corrected by volume. The dissimilarity by Dice index of the mapped ablation zone using deformable transformation vs rigid control was significantly (P = .04) higher at the ablation site than in the whole gland. CONCLUSIONS Our findings illustrate our method's ability to correct for deformation at the ablation site. The preliminary analysis suggests that deformable transformation computed from mutual information of preoperative and follow-up MRI is accurate in co-registration of MRI examinations performed before and after focal therapy. The ability to localize the previously ablated tissue in 3D space may improve targeting for image-guided follow-up biopsy within focal therapy protocols.
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Affiliation(s)
- Clément Orczyk
- The Prostate Unit, Department of Urology, University College London Hospitals, London, United Kingdom; Division of Urologic Oncology, Department of Urology, New York University Langone Medical Center, New York, NY; Normandie Université, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, 14000Caen, France; Department of Urology, University Hospital of Caen, Caen, France.
| | - Andrew B Rosenkrantz
- Department of Radiology, New York University Langone Medical Center, New York, NY
| | - Artem Mikheev
- Department of Radiology, New York University Langone Medical Center, New York, NY
| | - Arnauld Villers
- Department of Urology, Université Lille Nord de France, Lille, France
| | - Myriam Bernaudin
- Normandie Université, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, 14000Caen, France
| | - Samir S Taneja
- Division of Urologic Oncology, Department of Urology, New York University Langone Medical Center, New York, NY; Department of Radiology, New York University Langone Medical Center, New York, NY
| | - Samuel Valable
- Normandie Université, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, 14000Caen, France
| | - Henry Rusinek
- Department of Radiology, New York University Langone Medical Center, New York, NY
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Abstract
Multi-parametric magnetic resonance imaging (mp-MRI) has an increasingly important role in the diagnosis of prostate cancer. Due to the large amount of data and variations in mp-MRI, tumor detection can be affected by multiple factors, such as the observer's clinical experience, image quality, and appearance of the lesions. In order to improve the quantitative assessment of the disease and reduce the reporting time, various computer-aided diagnosis (CAD) systems have been designed to help radiologists identify lesions. This manuscript presents an overview of the literature regarding prostate CAD using mp-MRI, while focusing on the studies of the most recent five years. Current prostate CAD technologies and their utilization are discussed in this review.
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Das A, Bhattacharya M. Study on neurodegeneration at different stages using MR images: computational approach to registration process with optimisation techniques. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING: IMAGING & VISUALIZATION 2017. [DOI: 10.1080/21681163.2015.1036308] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments. Sci Rep 2016; 6:29906. [PMID: 27457670 PMCID: PMC4960603 DOI: 10.1038/srep29906] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2016] [Accepted: 06/24/2016] [Indexed: 11/11/2022] Open
Abstract
In applications involving large tissue specimens that have been sectioned into smaller tissue fragments, manual reconstruction of a “pseudo whole-mount” histological section (PWMHS) can facilitate (a) pathological disease annotation, and (b) image registration and correlation with radiological images. We have previously presented a program called HistoStitcher, which allows for more efficient manual reconstruction than general purpose image editing tools (such as Photoshop). However HistoStitcher is still manual and hence can be laborious and subjective, especially when doing large cohort studies. In this work we present AutoStitcher, a novel automated algorithm for reconstructing PWMHSs from digitized tissue fragments. AutoStitcher reconstructs (“stitches”) a PWMHS from a set of 4 fragments by optimizing a novel cost function that is domain-inspired to ensure (i) alignment of similar tissue regions, and (ii) contiguity of the prostate boundary. The algorithm achieves computational efficiency by performing reconstruction in a multi-resolution hierarchy. Automated PWMHS reconstruction results (via AutoStitcher) were quantitatively and qualitatively compared to manual reconstructions obtained via HistoStitcher for 113 prostate pathology sections. Distances between corresponding fiducials placed on each of the automated and manual reconstruction results were between 2.7%–3.2%, reflecting their excellent visual similarity.
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Commandeur F, Simon A, Mathieu R, Nassef M, Arango JDO, Rolland Y, Haigron P, de Crevoisier R, Acosta O. MRI to CT Prostate Registration for Improved Targeting in Cancer External Beam Radiotherapy. IEEE J Biomed Health Inform 2016; 21:1015-1026. [PMID: 27333613 DOI: 10.1109/jbhi.2016.2581881] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
External radiotherapy is a major clinical treatment for localized prostate cancer. Currently, computed tomography (CT) is used to delineate the prostate and to plan the radiotherapy treatment. However, CT images suffer from a poor soft-tissue contrast and do not allow an accurate organ delineation. On the contrary, magnetic resonance imaging (MRI) provides rich details and high soft-tissue contrast, allowing tumor detection. Thus, the intraindividual propagation of MRI delineations toward the planning CT may improve tumor targeting. In this paper, we introduce a new method to propagate MRI prostate delineations to the planning CT. In the first step, a random forest classification is performed to coarsely detect the prostate in the CT images, yielding a prostate probability membership for each voxel and a prostate hard segmentation. Then, the registration is performed using a new similarity metric which maximizes the probability and the collinearity between the normals of the manual registration (MR) existing contour and the contour resulting from the CT classification. The first study on synthetic data was performed to analyze the influence of the metric parameters with different levels of noise. Then, the method was also evaluated on real MR-CT data using manual alignments and intraprostatic fiducial markers and compared to a classically used mutual information (MI) approach. The proposed metric outperformed MI by 7% in terms of Dice score coefficient, by 3.14 mm the Hausdorff distance, and 2.13 mm the markers position errors. Finally, the impact of registration uncertainties on the treatment planning was evaluated, demonstrating the potential advantage of the proposed approach in a clinical setup to define a precise target.
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You JY, Lee HJ, Hwang SI, Bae YJ, Kim H, Hong H, Choe G. Value of T1/T2-weighted magnetic resonance imaging registration to reduce the postbiopsy hemorrhage effect for prostate cancer localization. Prostate Int 2015; 3:80-6. [PMID: 26473149 PMCID: PMC4588389 DOI: 10.1016/j.prnil.2015.06.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Accepted: 06/04/2015] [Indexed: 11/16/2022] Open
Abstract
Background The aim of this study was to evaluate the value of T1/T2-weighted imaging (T1/T2WI) registration to reduce the postbiopsy hemorrhage effect for prostate cancer localization on prostate magnetic resonance imaging (MRI). Methods Twenty-one men with pathology-proven prostate cancer who underwent preoperative MRI in a single institution were selected. The zonal anatomy was divided into 16 sections. T2WI, T1/T2-weighted registered imaging (T1/T2RI), T2WI combined with diffusion-weighted imaging (T2WI + DWI), and T1/T2RI combined with DWI (T1/T2RI + DWI) were scored for the likelihood of cancer by two radiology faculty members and two trainees, and were compared with histology results. Areas under the receiver operating characteristics curve (AUCs) were used to assess diagnostic accuracy. Results For the trainees (Reader 3 and Reader 4), the AUC values were significantly higher (P < 0.05) for T1/T2RI (0.60 and 0.62, respectively) than for T2WI (0.54 and 0.56, respectively) in tumor detection, whereas no significant difference was observed for faculty members. There was no significant difference in AUC values between T1/T2RI and T2WI + DWI for all readers except for Reader 1. There was no additional diagnostic benefit for adding DWI with T1/T2RI for all readers. Conclusions T1/T2WI registration is a feasible technique. For less experienced readers, T1/T2RI is better than T2WI in localization of prostate cancer.
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Affiliation(s)
- Ja Yeon You
- Department of Radiology, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, South Korea
| | - Hak Jong Lee
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, South Korea ; Program in Nano Science and Technology, Department of Transdisciplinary Studies, Seoul National University Graduate School of Convergence Science and Technology, Suwon, South Korea
| | - Sung Il Hwang
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Yun Jung Bae
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Hannah Kim
- Department of Computer Science and Engineering, Seoul Women's University, Seoul, South Korea
| | - Helen Hong
- Department of Multimedia Engineering, Seoul Women's University, Seoul, South Korea
| | - Gheeyoung Choe
- Department of Pathology, Seoul National University College of Medicine and Seoul National University Bundang Hospital, Seongnam, South Korea
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Athavale P, Xu R, Radau P, Nachman A, Wright GA. Multiscale properties of weighted total variation flow with applications to denoising and registration. Med Image Anal 2015; 23:28-42. [PMID: 25958027 DOI: 10.1016/j.media.2015.04.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 04/14/2015] [Accepted: 04/16/2015] [Indexed: 11/25/2022]
Abstract
Images consist of structures of varying scales: large scale structures such as flat regions, and small scale structures such as noise, textures, and rapidly oscillatory patterns. In the hierarchical (BV, L(2)) image decomposition, Tadmor, et al. (2004) start with extracting coarse scale structures from a given image, and successively extract finer structures from the residuals in each step of the iterative decomposition. We propose to begin instead by extracting the finest structures from the given image and then proceed to extract increasingly coarser structures. In most images, noise could be considered as a fine scale structure. Thus, starting the image decomposition with finer scales, rather than large scales, leads to fast denoising. We note that our approach turns out to be equivalent to the nonstationary regularization in Scherzer and Weickert (2000). The continuous limit of this procedure leads to a time-scaled version of total variation flow. Motivated by specific clinical applications, we introduce an image depending weight in the regularization functional, and study the corresponding weighted TV flow. We show that the edge-preserving property of the multiscale representation of an input image obtained with the weighted TV flow can be enhanced and localized by appropriate choice of the weight. We use this in developing an efficient and edge-preserving denoising algorithm with control on speed and localization properties. We examine analytical properties of the weighted TV flow that give precise information about the denoising speed and the rate of change of energy of the images. An additional contribution of the paper is to use the images obtained at different scales for robust multiscale registration. We show that the inherently multiscale nature of the weighted TV flow improved performance for registration of noisy cardiac MRI images, compared to other methods such as bilateral or Gaussian filtering. A clinical application of the multiscale registration algorithm is also demonstrated for aligning viability assessment magnetic resonance (MR) images from 8 patients with previous myocardial infarctions.
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Affiliation(s)
- Prashant Athavale
- Department of Mathematics, University of Toronto, Toronto, ON M5S 1A1, Canada; The Fields Institute, 222 College Street, Toronto, ON M5T 3J1, Canada.
| | - Robert Xu
- Schulich Heart Program and Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 2M9, Canada.
| | - Perry Radau
- Schulich Heart Program and Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada.
| | - Adrian Nachman
- Department of Mathematics, University of Toronto, Toronto, ON M5S 1A1, Canada; The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, 10 King's College Road, Toronto, ON M5S 3G4, Canada; Institute of Biomaterials & Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON M5S 3G9, Canada.
| | - Graham A Wright
- Schulich Heart Program and Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 2M9, Canada.
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Qin X, Wang S, Shen M, Zhang X, Lerakis S, Wagner MB, Fei B. Register cardiac fiber orientations from 3D DTI volume to 2D ultrasound image of rat hearts. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2015; 9415. [PMID: 26855466 DOI: 10.1117/12.2082317] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Two-dimensional (2D) ultrasound or echocardiography is one of the most widely used examinations for the diagnosis of cardiac diseases. However, it only supplies the geometric and structural information of the myocardium. In order to supply more detailed microstructure information of the myocardium, this paper proposes a registration method to map cardiac fiber orientations from three-dimensional (3D) magnetic resonance diffusion tensor imaging (MR-DTI) volume to the 2D ultrasound image. It utilizes a 2D/3D intensity based registration procedure including rigid, log-demons, and affine transformations to search the best similar slice from the template volume. After registration, the cardiac fiber orientations are mapped to the 2D ultrasound image via fiber relocations and reorientations. This method was validated by six images of rat hearts ex vivo. The evaluation results indicated that the final Dice similarity coefficient (DSC) achieved more than 90% after geometric registrations; and the inclination angle errors (IAE) between the mapped fiber orientations and the gold standards were less than 15 degree. This method may provide a practical tool for cardiologists to examine cardiac fiber orientations on ultrasound images and have the potential to supply additional information for diagnosis of cardiac diseases.
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Affiliation(s)
- Xulei Qin
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Silun Wang
- Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Ming Shen
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, GA
| | - Xiaodong Zhang
- Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Stamatios Lerakis
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, GA; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Mary B Wagner
- Department of Pediatrics, Emory University, Atlanta, GA
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA
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Qin X, Wang S, Shen M, Zhang X, Lerakis S, Wagner MB, Fei B. 3D in vivo imaging of rat hearts by high frequency ultrasound and its application in myofiber orientation wrapping. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2015; 9419. [PMID: 26412926 DOI: 10.1117/12.2082326] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Cardiac ultrasound plays an important role in the imaging of hearts in basic cardiovascular research and clinical examinations. 3D ultrasound imaging can provide the geometry or motion information of the heart. Especially, the wrapping of cardiac fiber orientations to the ultrasound volume could supply useful information on the stress distributions and electric action spreading. However, how to acquire 3D ultrasound volumes of the heart of small animals in vivo for cardiac fiber wrapping is still a challenging problem. In this study, we provide an approach to acquire 3D ultrasound volumes of the rat hearts in vivo. The comparison between both in vivo and ex vivo geometries indicated 90.1% Dice similarity. In this preliminary study, the evaluations of the cardiac fiber orientation wrapping errors were 24.7° for the acute angle error and were 22.4° for the inclination angle error. This 3D ultrasound imaging and fiber orientation estimation technique have potential applications in cardiac imaging.
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Affiliation(s)
- Xulei Qin
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Silun Wang
- Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Ming Shen
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, GA
| | - Xiaodong Zhang
- Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Stamatios Lerakis
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, GA ; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Mary B Wagner
- Department of Pediatrics, Emory University, Atlanta, GA
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA
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Mazaheri Y, Afaq AA, Jung SI, Goldman DA, Wang L, Aslan H, Zelefsky MJ, Akin O, Hricak H. Volume and landmark analysis: comparison of MRI measurements obtained with an endorectal coil and with a phased-array coil. Clin Radiol 2014; 70:379-86. [PMID: 25554540 DOI: 10.1016/j.crad.2014.12.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Revised: 11/26/2014] [Accepted: 12/03/2014] [Indexed: 11/27/2022]
Abstract
AIM To compare prostate volumes and distances between anatomical landmarks on MRI images obtained with a phased-array coil (PAC) only and with a PAC and an endorectal coil (ERC). MATERIALS AND METHODS Informed consent was waived for this Health Insurance Portability and Accountability Act-compliant study. Fifty-nine men underwent PAC-MRI and ERC-MRI at 1.5 (n = 3) or 3 T (n = 56). On MRI images, two radiologists independently measured prostate volume and distances between the anterior rectal wall (ARW) and symphysis pubis at the level of the verumontanum; ARW and symphysis pubis at the level of the mid-symphysis pubis; and bladder neck and mid-symphysis pubis. Differences between measurements from PAC-MRI and ERC-MRI were assessed with the Wilcoxon RANK SUM test. Inter-reader agreement was assessed using the concordance correlation coefficient (CCC). RESULTS Differences in prostate volume between PAC-MRI and ERC-MRI [median: -0.75 mm(3) (p = 0.10) and median: -0.84 mm(3) (p = 0.06) for readers 1 and 2, respectively] were not significant. For readers 1 and 2, median differences between distances were as follows: -10.20 and -12.75 mm, respectively, ARW to symphysis pubis at the level of the verumontanum; -6.60 and -6.08 mm, respectively, ARW to symphysis pubis at the level of the mid-symphysis pubis; -3 and -3 mm respectively, bladder neck to mid-symphysis pubis. All differences in distance were significant for both readers (p ≤ 0.0005). Distances were larger on PAC-MRI (p ≤ 0.0005). Inter-reader agreement regarding prostate volume was almost perfect on PAC-MRI (CCC: 0.99; 95% CI: 0.98-1.00) and ERC-MRI (CCC: 0.99; 95% CI: 0.99-1.00); inter-reader agreement for distance measurements varied (CCCs: 0.54-0.86). CONCLUSION Measurements of distances between anatomical landmarks differed significantly between ERC-MRI and PAC-MRI, although prostate volume measurements did not.
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Affiliation(s)
- Y Mazaheri
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA; Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
| | - A A Afaq
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - S I Jung
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - D A Goldman
- Department of Epidemiology & Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - L Wang
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - H Aslan
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - M J Zelefsky
- Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - O Akin
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - H Hricak
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
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Validation of the CT-MRI image registration with a dedicated phantom. Radiol Med 2014; 119:942-950. [PMID: 25024060 DOI: 10.1007/s11547-014-0392-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2013] [Accepted: 10/28/2013] [Indexed: 10/25/2022]
Abstract
PURPOSE The present study was aimed at verifying the automatic registration of the Focal (Elekta) platform with a dedicated phantom. MATERIALS AND METHODS A phantom that simulates the pelvis region in a stylised way and finalised to the registration of computed tomography-magnetic resonance images was designed and realised. After acquiring the two sets of images, the registration was performed both in automatic and manual mode to verify whether they were comparable. To test the repeatability of the automatic registration, some known rigid transformations were imposed to the original images. If the registration method works correctly, parameters which bring the images into alignment must always be the same. RESULTS Automatic registration performed by the software did not prove satisfactory, whereas if a specific tool [volume of interest (VOI) tool] allowing the calculation to be limited to the landmark region was used, the registration parameters were comparable with those of the manual registration. Regarding the repeatability of the automatic registration, the software brought the images in the correct alignment performing translations and rotations along the longitudinal axis up to 40°, while it was not satisfactory for rotations along the transverse axes. CONCLUSION The experimental results showed that in clinical application automatic registration is reliable if the VOI tool that includes visible landmarks in both studies is used. However, because the algorithm did not prove sensitive to rotations along the transverse axes, the position of the patient during the examinations plays a crucial role.
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Qin X, Lu G, Sechopoulos I, Fei B. Breast Tissue Classification in Digital Tomosynthesis Images Based on Global Gradient Minimization and Texture Features. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2014; 9034:90341V. [PMID: 25426271 PMCID: PMC4241347 DOI: 10.1117/12.2043828] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/27/2023]
Abstract
Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.
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Affiliation(s)
- Xulei Qin
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Guolan Lu
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA
| | - Ioannis Sechopoulos
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
- Winship Cancer Institute, Emory University, Atlanta, GA
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA
- Department of Mathematics & Computer Science, Emory University, Atlanta, GA
- Winship Cancer Institute, Emory University, Atlanta, GA
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Lu G, Halig L, Wang D, Chen ZG, Fei B. Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2014; 9036:90360S. [PMID: 25328640 PMCID: PMC4201054 DOI: 10.1117/12.2043805] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.
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Affiliation(s)
- Guolan Lu
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia
Institute of Technology and Emory University, Atlanta, GA
| | - Luma Halig
- Department of Hematology and Medical Oncology, Emory University,
Atlanta, GA
| | - Dongsheng Wang
- Department of Hematology and Medical Oncology, Emory University,
Atlanta, GA
| | - Zhuo Georgia Chen
- Department of Hematology and Medical Oncology, Emory University,
Atlanta, GA
| | - Baowei Fei
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia
Institute of Technology and Emory University, Atlanta, GA
- Department of Radiology and Imaging Sciences, Emory University,
Atlanta, GA
- Department of Mathematics & Computer Science, Emory University,
Atlanta, GA
- Winship Cancer Institute of Emory University, Atlanta, GA
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16
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Qin X, Wang S, Shen M, Zhang X, Wagner MB, Fei B. Mapping Cardiac Fiber Orientations from High-Resolution DTI to High-Frequency 3D Ultrasound. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2014; 9036:90361O. [PMID: 25328641 DOI: 10.1117/12.2043821] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
The orientation of cardiac fibers affects the anatomical, mechanical, and electrophysiological properties of the heart. Although echocardiography is the most common imaging modality in clinical cardiac examination, it can only provide the cardiac geometry or motion information without cardiac fiber orientations. If the patient's cardiac fiber orientations can be mapped to his/her echocardiography images in clinical examinations, it may provide quantitative measures for diagnosis, personalized modeling, and image-guided cardiac therapies. Therefore, this project addresses the feasibility of mapping personalized cardiac fiber orientations to three-dimensional (3D) ultrasound image volumes. First, the geometry of the heart extracted from the MRI is translated to 3D ultrasound by rigid and deformable registration. Deformation fields between both geometries from MRI and ultrasound are obtained after registration. Three different deformable registration methods were utilized for the MRI-ultrasound registration. Finally, the cardiac fiber orientations imaged by DTI are mapped to ultrasound volumes based on the extracted deformation fields. Moreover, this study also demonstrated the ability to simulate electricity activations during the cardiac resynchronization therapy (CRT) process. The proposed method has been validated in two rat hearts and three canine hearts. After MRI/ultrasound image registration, the Dice similarity scores were more than 90% and the corresponding target errors were less than 0.25 mm. This proposed approach can provide cardiac fiber orientations to ultrasound images and can have a variety of potential applications in cardiac imaging.
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Affiliation(s)
- Xulei Qin
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Silun Wang
- Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Ming Shen
- Department of Pediatrics, Emory University, Atlanta, GA
| | - Xiaodong Zhang
- Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Mary B Wagner
- Department of Pediatrics, Emory University, Atlanta, GA
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA
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Korsager AS, Carl J, Østergaard LR. MR-CT registration using a Ni-Ti prostate stent in image-guided radiotherapy of prostate cancer. Med Phys 2014; 40:061907. [PMID: 23718598 DOI: 10.1118/1.4807087] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE In image-guided radiotherapy of prostate cancer defining the clinical target volume often relies on magnetic resonance (MR). The task of transferring the clinical target volume from MR to standard planning computed tomography (CT) is not trivial due to prostate mobility. In this paper, an automatic local registration approach is proposed based on a newly developed removable Ni-Ti prostate stent. METHODS The registration uses the voxel similarity measure mutual information in a two-step approach where the pelvic bones are used to establish an initial registration for the local registration. RESULTS In a phantom study, the accuracy was measured to 0.97 mm and visual inspection showed accurate registration of all 30 data sets. The consistency of the registration was examined where translation and rotation displacements yield a rotation error of 0.41° ± 0.45° and a translation error of 1.67 ± 2.24 mm. CONCLUSIONS This study demonstrated the feasibility for an automatic local MR-CT registration using the prostate stent.
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Affiliation(s)
- Anne Sofie Korsager
- Department of Health Science and Technology, Aalborg University, Aalborg 9220, Denmark.
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18
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Tahmasebi AM, Sharifi R, Agarwal HK, Turkbey B, Bernardo M, Choyke P, Pinto P, Wood B, Kruecker J. A statistical model-based technique for accounting for prostate gland deformation in endorectal coil-based MR imaging. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2013; 2012:5412-5. [PMID: 23367153 DOI: 10.1109/embc.2012.6347218] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In prostate brachytherapy procedures, combining high-resolution endorectal coil (ERC)-MRI with Computed Tomography (CT) images has shown to improve the diagnostic specificity for malignant tumors. Despite such advantage, there exists a major complication in fusion of the two imaging modalities due to the deformation of the prostate shape in ERC-MRI. Conventionally, nonlinear deformable registration techniques have been utilized to account for such deformation. In this work, we present a model-based technique for accounting for the deformation of the prostate gland in ERC-MR imaging, in which a unique deformation vector is estimated for every point within the prostate gland. Modes of deformation for every point in the prostate are statistically identified using a set of MR-based training set (with and without ERC-MRI). Deformation of the prostate from a deformed (ERC-MRI) to a non-deformed state in a different modality (CT) is then realized by first calculating partial deformation information for a limited number of points (such as surface points or anatomical landmarks) and then utilizing the calculated deformation from a subset of the points to determine the coefficient values for the modes of deformations provided by the statistical deformation model. Using a leave-one-out cross-validation, our results demonstrated a mean estimation error of 1mm for a MR-to-MR registration.
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19
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Xu H, Lasso A, Guion P, Krieger A, Kaushal A, Singh AK, Pinto PA, Coleman J, Grubb RL, Lattouf JB, Menard C, Whitcomb LL, Fichtinger G. Accuracy analysis in MRI-guided robotic prostate biopsy. Int J Comput Assist Radiol Surg 2013; 8:937-44. [PMID: 23532560 DOI: 10.1007/s11548-013-0831-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2013] [Accepted: 03/11/2013] [Indexed: 10/27/2022]
Abstract
PURPOSE To assess retrospectively the clinical accuracy of an magnetic resonance imaging-guided robotic prostate biopsy system that has been used in the US National Cancer Institute for over 6 years. METHODS Series of 2D transverse volumetric MR image slices of the prostate both pre (high-resolution T2-weighted)- and post (low-resolution)- needle insertions were used to evaluate biopsy accuracy. A three-stage registration algorithm consisting of an initial two-step rigid registration followed by a B-spline deformable alignment was developed to capture prostate motion during biopsy. The target displacement (distance between planned and actual biopsy target), needle placement error (distance from planned biopsy target to needle trajectory), and biopsy error (distance from actual biopsy target to needle trajectory) were calculated as accuracy assessment. RESULTS A total of 90 biopsies from 24 patients were studied. The registrations were validated by checking prostate contour alignment using image overlay, and the results were accurate to within 2 mm. The mean target displacement, needle placement error, and clinical biopsy error were 5.2, 2.5, and 4.3 mm, respectively. CONCLUSION The biopsy error reported suggests that quantitative imaging techniques for prostate registration and motion compensation may improve prostate biopsy targeting accuracy.
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Affiliation(s)
- Helen Xu
- Queen's University, Kingston, ON, Canada,
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20
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Wooten WJ, Nye JA, Schuster DM, Nieh PT, Master VA, Votaw JR, Fei B. Accuracy Evaluation of a 3D Ultrasound-guided Biopsy System. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2013; 8671. [PMID: 24392206 DOI: 10.1117/12.2007695] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Early detection of prostate cancer is critical in maximizing the probability of successful treatment. Current systematic biopsy approach takes 12 or more randomly distributed core tissue samples within the prostate and can have a high potential, especially with early disease, for a false negative diagnosis. The purpose of this study is to determine the accuracy of a 3D ultrasound-guided biopsy system. Testing was conducted on prostate phantoms created from an agar mixture which had embedded markers. The phantoms were scanned and the 3D ultrasound system was used to direct the biopsy. Each phantom was analyzed with a CT scan to obtain needle deflection measurements. The deflection experienced throughout the biopsy process was dependent on the depth of the biopsy target. The results for markers at a depth of less than 20 mm, 20-30 mm, and greater than 30 mm were 3.3 mm, 4.7 mm, and 6.2 mm, respectively. This measurement encapsulates the entire biopsy process, from the scanning of the phantom to the firing of the biopsy needle. Increased depth of the biopsy target caused a greater deflection from the intended path in most cases which was due to an angular incidence of the biopsy needle. Although some deflection was present, this system exhibits a clear advantage in the targeted biopsy of prostate cancer and has the potential to reduce the number of false negative biopsies for large lesions.
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Affiliation(s)
- Walter J Wooten
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Jonathan A Nye
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - David M Schuster
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Peter T Nieh
- Department of Urology, Emory University School of Medicine, Atlanta, GA
| | - Viraj A Master
- Department of Urology, Emory University School of Medicine, Atlanta, GA
| | - John R Votaw
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology ; Department of Mathematics and Computer Science, Emory University, Atlanta, GA
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21
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Fei B, Yang X, Nye JA, Aarsvold JN, Raghunath N, Cervo M, Stark R, Meltzer CC, Votaw JR. MR∕PET quantification tools: registration, segmentation, classification, and MR-based attenuation correction. Med Phys 2012; 39:6443-54. [PMID: 23039679 DOI: 10.1118/1.4754796] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Combined MR∕PET is a relatively new, hybrid imaging modality. A human MR∕PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR∕PET for brain imaging. METHODS The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR∕PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [(11)C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. RESULTS For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. CONCLUSIONS MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR∕PET.
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Affiliation(s)
- Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA.
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22
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Fei B, Flask C, Wang H, Pi A, Wilson D, Shillingford J, Murcia N, Weimbs T, Duerk J. Image Segmentation, Registration and Visualization of Serial MR Images for Therapeutic Assessment of Polycystic Kidney Disease in Transgenic Mice. CONFERENCE PROCEEDINGS : ... ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL CONFERENCE 2012; 2006:467-9. [PMID: 17282217 DOI: 10.1109/iembs.2005.1616448] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In vivo small animal imaging provides a powerful tool for the study of a variety of diseases. Magnetic resonance imaging (MRI) has become an established technology for the assessment of therapies. In this study, we used high-resolution MRI to evaluate polycystic kidney disease (PKD) in transgenic mice. We used a customized mouse coil to acquire serial MR images from both wide-type and transgenic PKD mice immediately prior to, and 2-week and 4-week after therapy. We developed image segmentation, registration and visualization methods for this novel imaging application. We measured the kidney volumes for each mouse to assess the efficacy of the therapy. The segmentation results show that the kidney volumes are consistent, which are 348.7 ± 19.7 mm<sup>3</sup>for wild-type mice and 756.3 ± 44.1 mm<sup>3</sup>for transgenic mice, respectively. The image analysis methods provide a useful tool for this new application.
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Affiliation(s)
- Baowei Fei
- Department of Radiology, Case Western Reserve University & University Hospitals of Cleveland, USA
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23
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Dean CJ, Sykes JR, Cooper RA, Hatfield P, Carey B, Swift S, Bacon SE, Thwaites D, Sebag-Montefiore D, Morgan AM. An evaluation of four CT-MRI co-registration techniques for radiotherapy treatment planning of prone rectal cancer patients. Br J Radiol 2012; 85:61-8. [PMID: 22190750 DOI: 10.1259/bjr/11855927] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVES MRI is the preferred staging modality for rectal carcinoma patients. This work assesses the CT-MRI co-registration accuracy of four commercial rigid-body techniques for external beam radiotherapy treatment planning for patients treated in the prone position without fiducial markers. METHODS 17 patients with biopsy-proven rectal carcinoma were scanned with CT and MRI in the prone position without the use of fiducial markers. A reference co-registration was performed by consensus of a radiologist and two physicists. This was compared with two automated and two manual techniques on two separate treatment planning systems. Accuracy and reproducibility were analysed using a measure of target registration error (TRE) that was based on the average distance of the mis-registration between vertices of the clinically relevant gross tumour volume as delineated on the CT image. RESULTS An automated technique achieved the greatest accuracy, with a TRE of 2.3 mm. Both automated techniques demonstrated perfect reproducibility and were significantly faster than their manual counterparts. There was a significant difference in TRE between registrations performed on the two planning systems, but there were no significant differences between the manual and automated techniques. CONCLUSION For patients with rectal cancer, MRI acquired in the prone treatment position without fiducial markers can be accurately registered with planning CT. An automated registration technique offered a fast and accurate solution with associated uncertainties within acceptable treatment planning limits.
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Affiliation(s)
- C J Dean
- Department of Medical Physics, St James's Institute of Oncology, Leeds, UK.
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Zhang B, Arola DD, Roys S, Gullapalli RP. Three-dimensional elastic image registration based on strain energy minimization: application to prostate magnetic resonance imaging. J Digit Imaging 2011; 24:573-85. [PMID: 20552248 DOI: 10.1007/s10278-010-9306-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The use of magnetic resonance (MR) imaging in conjunction with an endorectal coil is currently the clinical standard for the diagnosis of prostate cancer because of the increased sensitivity and specificity of this approach. However, imaging in this manner provides images and spectra of the prostate in the deformed state because of the insertion of the endorectal coil. Such deformation may lead to uncertainties in the localization of prostate cancer during therapy. We propose a novel 3-D elastic registration procedure that is based on the minimization of a physically motivated strain energy function that requires the identification of similar features (points, curves, or surfaces) in the source and target images. The Gauss-Seidel method was used in the numerical implementation of the registration algorithm. The registration procedure was validated on synthetic digital images, MR images from prostate phantom, and MR images obtained on patients. The registration error, assessed by averaging the displacement of a fiducial landmark in the target to its corresponding point in the registered image, was 0.2 ± 0.1 pixels on synthetic images. On the prostate phantom and patient data, the registration errors were 1.0 ± 0.6 pixels (0.6 ± 0.4 mm) and 1.8 ± 0.7 pixels (1.1 ± 0.4 mm), respectively. Registration also improved image similarity (normalized cross-correlation) from 0.72 ± 0.10 to 0.96 ± 0.03 on patient data. Registration results on digital images, phantom, and prostate data in vivo demonstrate that the registration procedure can be used to significantly improve both the accuracy of localized therapies such as brachytherapy or external beam therapy and can be valuable in the longitudinal follow-up of patients after therapy.
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Affiliation(s)
- Bao Zhang
- Magnetic Resonance Research Center, Department of Diagnostic Radiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
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SHAO WEI, WU RUOYUN, THNG CHOONHUA, LING KECKVOON, NG WANSING. INTEGRATING MRI AND MRSI INFORMATION INTO TRUS-GUIDED ROBOTIC PROSTATE BIOPSY. INT J HUM ROBOT 2011. [DOI: 10.1142/s0219843606000874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The development of prostate biopsy robotics can make biopsies both automatic and accurate. However, intervention from urologists is still needed to define the location of biopsy cores. With the aid of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy imaging (MRSI) diagnosis information obtained pre-operationally, it is possible to guide the biopsy needle towards those sites where cancer is suspected, thereby achieving higher detection rates. In this paper, a deformable image registration method is presented for the purpose of merging MRI/MRSI and transrectal ultrasound (TRUS) images. Given the poor quality of ultrasound (US) images and the deformation occurring across modalites, a thin-plate spline transformation is used to match the prostate surfaces and thereafter their volumes. A deformable prostate phantom that simulates the condition in humans was also set up for validation purposes. Fifteen fiducial markers were implanted inside the phantom prostate to act as the reference of "ground truth." The phantom study shows that our method can achieve an accuracy around 1.28 ± 0.50 mm, with voxel dimensions of 0.5 × 0.5 × 0.5 mm3. This result is promising since none of the knowledge about the interior prostate is utilized in the algorithm. Experimental results on patient data are also presented.
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Affiliation(s)
- WEI SHAO
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
| | - RUOYUN WU
- Clinical Research Unit, Tan Tock Seng Hospital, Singapore
| | - CHOON HUA THNG
- Department of Diagnostic Imaging, National Cancer Centre, Singapore
| | - KECK VOON LING
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
| | - WAN SING NG
- School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore
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Pan M, Tang J, Xiong Q. Medical image registration using fuzzy theory. Comput Methods Biomech Biomed Engin 2011; 15:721-34. [PMID: 21442490 DOI: 10.1080/10255842.2011.557372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Mutual information (MI)-based registration, which uses MI as the similarity measure, is a representative method in medical image registration. It has an excellent robustness and accuracy, but with the disadvantages of a large amount of calculation and a long processing time. In this paper, by computing the medical image moments, the centroid is acquired. By applying fuzzy c-means clustering, the coordinates of the medical image are divided into two clusters to fit a straight line, and the rotation angles of the reference and floating images are computed, respectively. Thereby, the initial values for registering the images are determined. When searching the optimal geometric transformation parameters, we put forward the two new concepts of fuzzy distance and fuzzy signal-to-noise ratio (FSNR), and we select FSNR as the similarity measure between the reference and floating images. In the experiments, the Simplex method is chosen as multi-parameter optimisation. The experimental results show that this proposed method has a simple implementation, a low computational cost, a fast registration and good registration accuracy. Moreover, it can effectively avoid trapping into the local optima. It is adapted to both mono-modality and multi-modality image registrations.
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Affiliation(s)
- Meisen Pan
- College of Computer Science and Technology, Hunan University of Arts and Science, Changde, Hunan Province, 415000, PR China.
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27
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Fei B, Duerk JL, Wilson DL. Automatic 3D Registration for Interventional MRI-Guided Treatment of Prostate Cancer. ACTA ACUST UNITED AC 2010. [DOI: 10.3109/10929080209146034] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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28
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Fang YHD, Asthana P, Salinas C, Huang HM, Muzic RF. Integrated software environment based on COMKAT for analyzing tracer pharmacokinetics with molecular imaging. J Nucl Med 2009; 51:77-84. [PMID: 20008992 DOI: 10.2967/jnumed.109.064824] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
UNLABELLED An integrated software package, Compartment Model Kinetic Analysis Tool (COMKAT), is presented in this report. METHODS COMKAT is an open-source software package with many functions for incorporating pharmacokinetic analysis in molecular imaging research and has both command-line and graphical user interfaces. RESULTS With COMKAT, users may load and display images, draw regions of interest, load input functions, select kinetic models from a predefined list, or create a novel model and perform parameter estimation, all without having to write any computer code. For image analysis, COMKAT image tool supports multiple image file formats, including the Digital Imaging and Communications in Medicine (DICOM) standard. Image contrast, zoom, reslicing, display color table, and frame summation can be adjusted in COMKAT image tool. It also displays and automatically registers images from 2 modalities. Parametric imaging capability is provided and can be combined with the distributed computing support to enhance computation speeds. For users without MATLAB licenses, a compiled, executable version of COMKAT is available, although it currently has only a subset of the full COMKAT capability. Both the compiled and the noncompiled versions of COMKAT are free for academic research use. Extensive documentation, examples, and COMKAT itself are available on its wiki-based Web site, http://comkat.case.edu. Users are encouraged to contribute, sharing their experience, examples, and extensions of COMKAT. CONCLUSION With integrated functionality specifically designed for imaging and kinetic modeling analysis, COMKAT can be used as a software environment for molecular imaging and pharmacokinetic analysis.
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Affiliation(s)
- Yu-Hua Dean Fang
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Chen X, Gilkeson RC, Fei B. Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection. Med Phys 2008; 34:4934-43. [PMID: 18196818 DOI: 10.1118/1.2805994] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DEDR). CT is an established tool for the detection of cardiac calcification. DEDR could be a cost-effective alternative screening tool. In order to utilize CT as the "gold standard" to evaluate the capability of DEDR images for the detection and localization of calcium, we developed an automatic, intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DEDR images. To generate digitally reconstructed radiography (DRR) from the CT volumes, we developed several projection algorithms using the fast shear-warp method. In particular, we created a Gaussian-weighted projection for this application. We used normalized mutual information (NMI) as the similarity measurement. Simulated projection images from CT values were fused with the corresponding DEDR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with a translation difference of less than 0.8 mm and a rotation difference of less than 0.2 degrees. For physical phantom images, the registration accuracy is 0.43 +/- 0.24 mm. Color overlay and 3D visualization of clinical images show that the two images registered well. The NMI values between the DRR and DEDR images improved from 0.21 +/- 0.03 before registration to 0.25 +/- 0.03 after registration. Registration errors measured from anatomic markers decreased from 27.6 +/- 13.6 mm before registration to 2.5 +/- 0.5 mm after registration. Our results show that the automatic 3D-to-2D registration is accurate and robust. This technique can provide a useful tool for correlating DEDR with CT images for screening coronary artery calcification.
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Affiliation(s)
- Xiang Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio 44106, USA
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Fei B, Chen X, Wang H, Sabol JM, DuPont E, Gilkeson RC. Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases. CONFERENCE PROCEEDINGS : ... ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL CONFERENCE 2008; 2006:1976-9. [PMID: 17945687 DOI: 10.1109/iembs.2006.259888] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We are investigating image processing and analysis techniques to improve the ability of dual-energy digital radiography (DR) for the detection of cardiac calcification. Computed tomography (CT) is an established tool for the diagnosis of coronary artery diseases. Dual-energy digital radiography could be a cost-effective alternative. In this study, we use three-dimensional (3D) CT images as the "gold standard" to evaluate the DR X-ray images for calcification detection. To this purpose, we developed an automatic registration method for 3D CT volumes and two-dimensional (2D) X-ray images. We call this 3D-to-2D registration. We first use a 3D CT image volume to simulate X-ray projection images and then register them with X-ray images. The registered CT projection images are then used to aid the interpretation dual-energy X-ray images for the detection of cardiac calcification. We acquired both CT and X-ray images from patients with coronary artery diseases. Experimental results show that the 3D-to-2D registration is accurate and useful for this new application.
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Affiliation(s)
- Baowei Fei
- Dept. of Radiol. & Biomed. Eng., Case Western Reserve Univ., Cleveland, OH 44106, USA.
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Abstract
In this article the current issues of diagnosis and detection of prostate cancer are reviewed. The limitations for current techniques are highlighted and some possible solutions with MR imaging and MR-guided biopsy approaches are reviewed. There are several different biopsy approaches under investigation. These include transperineal open magnet approaches to closed-bore 1.5T transrectal biopsies. The imaging, image processing, and tracking methods are also discussed. In the arena of therapy, MR guidance has been used in conjunction with radiation methods, either brachytherapy or external delivery. The principles of the radiation treatment, the toxicities, and use of images are outlined. The future role of imaging and image-guided interventions lie with providing a noninvasive surrogate for cancer surveillance or monitoring treatment response. The shift to minimally invasive focal therapies has already begun and will be very exciting when MR-guided focused ultrasound surgery reaches its full potential.
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Affiliation(s)
- Clare Tempany
- Department of Radiology, Brigham & Women's Hospital, Boston, MA 02115, USA.
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Alterovitz R, Goldberg K, Kurhanewicz J, Pouliot J, Hsu IC. Image registration for prostate MR spectroscopy using modeling and optimization of force and stiffness parameters. CONFERENCE PROCEEDINGS : ... ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL CONFERENCE 2007; 2004:1722-5. [PMID: 17272037 DOI: 10.1109/iembs.2004.1403517] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
We develop an image registration system based on biomechanical modeling of the prostate and surrounding tissues to register cancerous tumor locations for targeted prostate brachytherapy treatment planning. Cancerous tumors can be identified using magnetic resonance spectroscopy (MRS) imaging, which is acquired with an endorectal probe that causes significant nonlinear deformation of the prostate. The probe is removed during magnetic resonance (MR) imaging for brachytherapy planning and therapy. Given 2-dimensional segmented MR and MRS images, our finite element based model defines a mapping between the probe-in/out images by estimating the deformation of the prostate and surrounding tissues due to endorectal probe insertion and balloon inflation. Treating uncertain patient-specific model parameters for tissue stiffness and external forces as variables, we compute a locally optimal solution to maximize image registration quality. We visualize results by applying the computed mapping to the MR image to generate a deformed MR image. We compare deformed MR images to corresponding MRS images for 5 patients and obtain an average dice similarity coefficient (DSC) of 95.6% for the prostate. Using the mapping, we warp a regular spectroscopy grid from the MRS image to the probe-out MR image for use during treatment planning.
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Affiliation(s)
- Ron Alterovitz
- Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA, USA
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Chen X, Gilkeson R, Fei B. Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2007; 6512. [PMID: 24386527 DOI: 10.1117/12.710192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 ± 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 ± 0.03 to 0.25 ± 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification.
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Affiliation(s)
- Xiang Chen
- Case Western Reserve University and Xi'an Jiaotong University
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34
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Salvado O, Wilson DL. Removal of local and biased global maxima in intensity-based registration. Med Image Anal 2006; 11:183-96. [PMID: 17280864 DOI: 10.1016/j.media.2006.12.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2006] [Revised: 08/21/2006] [Accepted: 12/15/2006] [Indexed: 11/25/2022]
Abstract
Intensity based registration (e.g., mutual information) suffers from a scalloping artifact giving rise to local maxima and sometimes a biased global maximum in a similarity objective function. Here, we demonstrate that scalloping is principally due to the noise reduction filtering that occurs when image samples are interpolated. Typically at a much smaller scale (100 times less in our test cases), there are also fluctuations in the similarity objective function due to interpolation of the signal and to sampling of a continuous, band-limited image signal. Focusing on the larger problem from noise, we show that this phenomenon can even bias global maxima, giving inaccurate registrations. This phenomenon is readily seen when one registers an image onto itself with different noise realizations but is absent when the same noise realization is present in both images. For linear interpolation, local maxima and global bias are removed if one filters the interpolated image using a new constant variance filter for linear interpolation (cv-lin filter), which equalizes the variance across the interpolated image. We use 2D synthetic and MR images and characterize the effect of cv-lin on similarity objective functions. With a reduction of local and biased maxima, image registration becomes more robust and accurate. An efficient implementation adds insignificant computation time per iteration, and because optimization proceeds more smoothly, sometimes fewer iterations are needed.
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Affiliation(s)
- Olivier Salvado
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
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Takao M, Sugano N, Nishii T, Tanaka H, Masumoto J, Miki H, Sato Y, Tamura S, Yoshikawa H. Application of three-dimensional magnetic resonance image registration for monitoring hip joint diseases. Magn Reson Imaging 2006; 23:665-70. [PMID: 16051041 DOI: 10.1016/j.mri.2005.02.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2004] [Accepted: 02/03/2005] [Indexed: 11/26/2022]
Abstract
The purpose of this study was to estimate the accuracy of a method in which three-dimensional (3D) magnetic resonance (MR) volume registration is used for monitoring hip joint disease. Data were analyzed using a normalized cross-correlation (NCC) algorithm involving a user-selected 3D box including the proximal femur. Most of the femoral head was not included in the 3D box because it can become deformed during the course of disease. The accuracy of registration around the femoral head was evaluated using five phantoms and clinical MR data of 17 patients with hip joint disease. In the phantom experiment, registration accuracy was evaluated using four fiducial markers attached to the femoral head. In the experiment using clinical data, registration accuracy was evaluated using a landmark in the femoral head. The registration accuracy in the phantom and clinical experiment was 0.43+/-0.18 mm (S.D.) and 1.12+/-0.46 mm (S.D.), respectively. The former is a value less than half the minimum dimension of a voxel (1.25 x 1.25 x 1.0 mm). Although the latter is slightly larger than the minimum dimension of a voxel, actual errors would be smaller because of the uncertainty in landmark localization. In conclusion, the present method based on an NCC algorithm can be used to accurately register serial MR images of the femoral heads with an error on the order of a voxel. We believe that this method is sufficiently accurate for monitoring hip joint diseases.
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Affiliation(s)
- Masaki Takao
- Department of Orthopaedic Surgery, Osaka University Graduate School of Medicine, Osaka 565-0871, Japan.
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36
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Xing L, Thorndyke B, Schreibmann E, Yang Y, Li TF, Kim GY, Luxton G, Koong A. Overview of image-guided radiation therapy. Med Dosim 2006; 31:91-112. [PMID: 16690451 DOI: 10.1016/j.meddos.2005.12.004] [Citation(s) in RCA: 271] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2005] [Indexed: 12/21/2022]
Abstract
Radiation therapy has gone through a series of revolutions in the last few decades and it is now possible to produce highly conformal radiation dose distribution by using techniques such as intensity-modulated radiation therapy (IMRT). The improved dose conformity and steep dose gradients have necessitated enhanced patient localization and beam targeting techniques for radiotherapy treatments. Components affecting the reproducibility of target position during and between subsequent fractions of radiation therapy include the displacement of internal organs between fractions and internal organ motion within a fraction. Image-guided radiation therapy (IGRT) uses advanced imaging technology to better define the tumor target and is the key to reducing and ultimately eliminating the uncertainties. The purpose of this article is to summarize recent advancements in IGRT and discussed various practical issues related to the implementation of the new imaging techniques available to radiation oncology community. We introduce various new IGRT concepts and approaches, and hope to provide the reader with a comprehensive understanding of the emerging clinical IGRT technologies. Some important research topics will also be addressed.
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Affiliation(s)
- Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305-5847, USA
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37
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Skerl D, Likar B, Pernus F. A protocol for evaluation of similarity measures for rigid registration. IEEE TRANSACTIONS ON MEDICAL IMAGING 2006; 25:779-91. [PMID: 16768242 DOI: 10.1109/tmi.2006.874963] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
The accuracy and robustness of a registration method depend on a number of factors, such as imaging modality, image content and image degrading effects, the class of spatial transformation used for registration, similarity measure, optimization, and numerous implementation details. The complex interdependence of these factors makes the assessment of the influence of a particular factor on registration difficult, although it is often desirable to have some estimate of such influences prior to registration. The similarity measure used to create the cost function is one of the factors that most influences the quality of registration. Traditionally, limited information on the behavior of a similarity measure is obtained either by studying the quality of the final registration or by drawing plots of similarity measure values obtained by translating or rotating one image relative to the "gold standard." In this paper, we present a protocol for a more thorough, optimization-independent, and systematic statistical evaluation of similarity measures. This protocol estimates a similarity measure's capture range, the number, location and extent of local optima, and the accuracy and distinctiveness of the global optimum. To show that the proposed evaluation protocol is viable, we have conducted several experiments with nine similarity measures and real computed tomography and magnetic resonance (MR) images of a spine phantom, MR brain images, and MR and positron emission tomography brain images, for which "gold standard" registrations were available. We have also studied the impact of histogram bin size on the behavior of nine similarity measures. The proposed evaluation protocol is useful for selecting the best similarity measure and corresponding optimization method for a particular application, as well as for studying the influence of sampling, interpolation, histogram bin size, partial image overlap, and image degradation, such as noise, intensity inhomogeneity, and geometrical distortions on the behavior of a similarity measure.
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Affiliation(s)
- Darko Skerl
- University of Ljubljana, Faculty of Electrical Engineering, Slovenia.
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Alterovitz R, Goldberg K, Pouliot J, Hsu ICJ, Kim Y, Noworolski SM, Kurhanewicz J. Registration of MR prostate images with biomechanical modeling and nonlinear parameter estimation. Med Phys 2006; 33:446-54. [PMID: 16532952 DOI: 10.1118/1.2163391] [Citation(s) in RCA: 69] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) have been shown to be very useful for identifying prostate cancers. For high sensitivity, the MRI/MRSI examination is often acquired with an endorectal probe that may cause a substantial deformation of the prostate and surrounding soft tissues. Such a probe is removed prior to radiation therapy treatment. To register diagnostic probe-in magnetic resonance (MR) images to therapeutic probe-out MR images for treatment planning, a new deformable image registration method is developed based on biomechanical modeling of soft tissues and estimation of uncertain tissue parameters using nonlinear optimization. Given two-dimensional (2-D) segmented probe-in and probe-out images, a finite element method (FEM) is used to estimate the deformation of the prostate and surrounding tissues due to displacements and forces resulting from the endorectal probe. Since FEM requires tissue stiffness properties and external force values as input, the method estimates uncertain parameters using nonlinear local optimization. The registration method is evaluated using images from five balloon and five rigid endorectal probe patient cases. It requires on average 37 s of computation time on a 1.6 GHz Pentium-M PC. Comparing the prostate outline in deformed probe-out images to corresponding probe-in images, the method obtains a mean Dice Similarity Coefficient (DSC) of 97.5% for the balloon probe cases and 98.1% for the rigid probe cases. The method improves significantly over previous methods (P < 0.05) with greater improvement for balloon probe cases with larger tissue deformations.
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Affiliation(s)
- Ron Alterovitz
- Department of Industrial Engineering and Operations Research, University of California, Berkeley, 4141 Etcheverry Hall, Berkeley, California 94720-1777, USA.
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Pallotta S, Bucciolini M, Russo S, Talamonti C, Cinzia T, Biti G. Accuracy evaluation of image registration and segmentation tools used in conformal treatment planning of prostate cancer. Comput Med Imaging Graph 2005; 30:1-7. [PMID: 16377131 DOI: 10.1016/j.compmedimag.2005.10.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2005] [Revised: 08/24/2005] [Indexed: 10/25/2022]
Abstract
Segmentation and registration tools are commonly used in radiotherapy for target and at risk organs localisation. In this work the performances of three different segmentation tools and of a surface matching registration technique, used on computed tomography (CT) and magnetic resonance (MR) images for the treatment planning of conformal prostate carcinoma, are studied. The accuracy of the segmentation and registration tools was evaluated by phantom experiment and on patient data, respectively. A preliminary estimate of MR image distortion was also performed.
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Affiliation(s)
- Stefania Pallotta
- Department of Clinical Physiopathology, Medical Physics Unit, University of Florence, Florence Italy.
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Fei B, Duerk JL, Sodee DB, Wilson DL. Semiautomatic nonrigid registration for the prostate and pelvic MR volumes. Acad Radiol 2005; 12:815-24. [PMID: 16039535 DOI: 10.1016/j.acra.2005.03.063] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2004] [Revised: 03/14/2005] [Accepted: 03/15/2005] [Indexed: 11/22/2022]
Abstract
RATIONALE AND OBJECTIVES Three-dimensional (3D) nonrigid image registration for potential applications in prostate cancer treatment and interventional magnetic resonance (iMRI) imaging-guided therapies were investigated. MATERIALS AND METHODS An almost fully automated 3D nonrigid registration algorithm using mutual information and a thin plate spline (TPS) transformation for MR images of the prostate and pelvis were created and evaluated. In the first step, an automatic rigid body registration with special features was used to capture the global transformation. In the second step, local feature points (FPs) were registered using mutual information. An operator entered only five FPs located at the prostate center, left and right hip joints, and left and right distal femurs. The program automatically determined and optimized other FPs at the external pelvic skin surface and along the femurs. More than 600 control points were used to establish a TPS transformation for deformation of the pelvic region and prostate. Ten volume pairs were acquired from three volunteers in the diagnostic (supine) and treatment positions (supine with legs raised). RESULTS Various visualization techniques showed that warping rectified the significant pelvic misalignment by the rigid-body method. Gray-value measures of registration quality, including mutual information, correlation coefficient, and intensity difference, all improved with warping. The distance between prostate 3D centroids was 0.7 +/- 0.2 mm after warping compared with 4.9 +/- 3.4 mm with rigid-body registration. CONCLUSION Semiautomatic nonrigid registration works better than rigid-body registration when patient position is changed greatly between acquisitions. It could be a useful tool for many applications in the management of prostate.
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Affiliation(s)
- Baowei Fei
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, OH 44106, USA.
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Li X, Zhang P, Brisman R, Kutcher G. Use of simulated annealing for optimization of alignment parameters in limited MRI acquisition volumes of the brain. Med Phys 2005; 32:2363-2370. [PMID: 16121594 DOI: 10.1118/1.1944287] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2004] [Revised: 04/08/2005] [Accepted: 05/06/2005] [Indexed: 11/07/2022] Open
Abstract
Studies suggest that clinical outcomes are improved in repeat trigeminal neuralgia (TN) Gamma Knife radiosurgery if a different part of the nerve from the previous radiosurgery is treated. The MR images taken in the first and repeat radiosurgery need to be coregistered to map the first radiosurgery volume onto the second treatment planning image. We propose a fully automatic and robust three-dimensional (3-D) mutual information- (MI-) based registration method engineered by a simulated annealing (SA) optimization technique. Commonly, Powell's method and Downhill simplex (DS) method are most popular in optimizing the MI objective function in medical image registration applications. However, due to the nonconvex property of the MI function, robustness of those two methods is questionable, especially for our cases, where only 28 slices of MR T1 images were utilized. Our SA method obtained successful registration results for all the 41 patients recruited in this study. On the other hand, Powell's method and the DS method failed to provide satisfactory registration for 11 patients and 9 patients, respectively. The overlapping volume ratio (OVR) is defined to quantify the degree of the partial volume overlap between the first and second MR scan. Statistical results from a logistic regression procedure demonstrated that the probability of a success of Powell's method tends to decrease as OVR decreases. The rigid registration with Powell's or the DS method is not suitable for the TN radiosurgery application, where OVR is likely to be low. In summary, our experimental results demonstrated that the MI-based registration method with the SA optimization technique is a robust and reliable option when the number of slices in the imaging study is limited.
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Affiliation(s)
- Xiang Li
- Department of Radiation Oncology, Columbia University, New York, New York 10032, USA
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Ceylan C, van der Heide UA, Bol GH, Lagendijk JJW, Kotte ANTJ. Assessment of rigid multi-modality image registration consistency using the multiple sub-volume registration (MSR) method. Phys Med Biol 2005; 50:N101-8. [PMID: 15876660 DOI: 10.1088/0031-9155/50/10/n01] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Registration of different imaging modalities such as CT, MRI, functional MRI (fMRI), positron (PET) and single photon (SPECT) emission tomography is used in many clinical applications. Determining the quality of any automatic registration procedure has been a challenging part because no gold standard is available to evaluate the registration. In this note we present a method, called the 'multiple sub-volume registration' (MSR) method, for assessing the consistency of a rigid registration. This is done by registering sub-images of one data set on the other data set, performing a crude non-rigid registration. By analysing the deviations (local deformations) of the sub-volume registrations from the full registration we get a measure of the consistency of the rigid registration. Registration of 15 data sets which include CT, MR and PET images for brain, head and neck, cervix, prostate and lung was performed utilizing a rigid body registration with normalized mutual information as the similarity measure. The resulting registrations were classified as good or bad by visual inspection. The resulting registrations were also classified using our MSR method. The results of our MSR method agree with the classification obtained from visual inspection for all cases (p < 0.02 based on ANOVA of the good and bad groups). The proposed method is independent of the registration algorithm and similarity measure. It can be used for multi-modality image data sets and different anatomic sites of the patient.
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Affiliation(s)
- C Ceylan
- Department of Radiotherapy, University Medical Center Utrecht, The Netherlands
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43
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Lian J, Xing L, Hunjan S, Dumoulin C, Levin J, Lo A, Watkins R, Rohling K, Giaquinto R, Kim D, Spielman D, Daniel B. Mapping of the prostate in endorectal coil-based MRI/MRSI and CT: A deformable registration and validation study. Med Phys 2004; 31:3087-94. [PMID: 15587662 DOI: 10.1118/1.1806292] [Citation(s) in RCA: 64] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
The endorectal coil is being increasingly used in magnetic resonance imaging (MRI) and MR spectroscopic imaging (MRSI) to obtain anatomic and metabolic images of the prostate with high signal-to-noise ratio (SNR). In practice, however, the use of endorectal probe inevitably distorts the prostate and other soft tissue organs, making the analysis and the use of the acquired image data in treatment planning difficult. The purpose of this work is to develop a deformable image registration algorithm to map the MRI/MRSI information obtained using an endorectal probe onto CT images and to verify the accuracy of the registration by phantom and patient studies. A mapping procedure involved using a thin plate spline (TPS) transformation was implemented to establish voxel-to-voxel correspondence between a reference image and a floating image with deformation. An elastic phantom with a number of implanted fiducial markers was designed for the validation of the quality of the registration. Radiographic images of the phantom were obtained before and after a series of intentionally introduced distortions. After mapping the distorted phantom to the original one, the displacements of the implanted markers were measured with respect to their ideal positions and the mean error was calculated. In patient studies, CT images of three prostate patients were acquired, followed by 3 Tesla (3 T) MR images with a rigid endorectal coil. Registration quality was estimated by the centroid position displacement and image coincidence index (CI). Phantom and patient studies show that TPS-based registration has achieved significantly higher accuracy than the previously reported method based on a rigid-body transformation and scaling. The technique should be useful to map the MR spectroscopic dataset acquired with ER probe onto the treatment planning CT dataset to guide radiotherapy planning.
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Affiliation(s)
- J Lian
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305, USA.
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Smitsmans MHP, Wolthaus JWH, Artignan X, de Bois J, Jaffray DA, Lebesque JV, van Herk M. Automatic localization of the prostate for on-line or off-line image-guided radiotherapy. Int J Radiat Oncol Biol Phys 2004; 60:623-35. [PMID: 15380600 DOI: 10.1016/j.ijrobp.2004.05.027] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2003] [Revised: 05/10/2004] [Accepted: 05/14/2004] [Indexed: 11/19/2022]
Abstract
PURPOSE With higher radiation dose, higher cure rates have been reported in prostate cancer patients. The extra margin needed to account for prostate motion, however, limits the level of dose escalation, because of the presence of surrounding organs at risk. Knowledge of the precise position of the prostate would allow significant reduction of the treatment field. Better localization of the prostate at the time of treatment is therefore needed, e.g. using a cone-beam computed tomography (CT) system integrated with the linear accelerator. Localization of the prostate relies upon manual delineation of contours in successive axial CT slices or interactive alignment and is fairly time-consuming. A faster method is required for on-line or off-line image-guided radiotherapy, because of prostate motion, for patient throughput and efficiency. Therefore, we developed an automatic method to localize the prostate, based on 3D gray value registration. METHODS AND MATERIALS A study was performed on conventional repeat CT scans of 19 prostate cancer patients to develop the methodology to localize the prostate. For each patient, 8-13 repeat CT scans were made during the course of treatment. First, the planning CT scan and the repeat CT scan were registered onto the rigid bony structures. Then, the delineated prostate in the planning CT scan was enlarged by an optimum margin of 5 mm to define a region of interest in the planning CT scan that contained enough gray value information for registration. Subsequently, this region was automatically registered to a repeat CT scan using 3D gray value registration to localize the prostate. The performance of automatic prostate localization was compared to prostate localization using contours. Therefore, a reference set was generated by registering the delineated contours of the prostates in all scans of all patients. Gray value registrations that showed large differences with respect to contour registrations were detected with a chi(2) analysis and were removed from the data set before further analysis. RESULTS Comparing gray value registration to contour registration, we found a success rate of 91%. The accuracy for rotations around the left-right, cranial-caudal, and anterior-posterior axis was 2.4 degrees, 1.6 degrees, and 1.3 degrees (1 SD), respectively, and for translations along these axes 0.7, 1.3, and 1.2 mm (1 SD), respectively. A large part of the error is attributed to uncertainty in the reference contour set. Automatic prostate localization takes about 45 seconds on a 1.7 GHz Pentium IV personal computer. CONCLUSIONS This newly developed method localizes the prostate quickly, accurately, and with a good success rate, although visual inspection is still needed to detect outliers. With this approach, it will be possible to correct on-line or off-line for prostate movement. Combined with the conformity of intensity-modulated dose distributions, this method might permit dose escalation beyond that of current conformal approaches, because margins can be safely reduced.
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Affiliation(s)
- Monique H P Smitsmans
- Department of Radiotherapy, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Amsterdam, The Netherlands
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Pluim JPW, Maintz JBA, Viergever MA. Mutual-information-based registration of medical images: a survey. IEEE TRANSACTIONS ON MEDICAL IMAGING 2003; 22:986-1004. [PMID: 12906253 DOI: 10.1109/tmi.2003.815867] [Citation(s) in RCA: 1057] [Impact Index Per Article: 50.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
An overview is presented of the medical image processing literature on mutual-information-based registration. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. Methods are classified according to the different aspects of mutual-information-based registration. The main division is in aspects of the methodology and of the application. The part on methodology describes choices made on facets such as preprocessing of images, gray value interpolation, optimization, adaptations to the mutual information measure, and different types of geometrical transformations. The part on applications is a reference of the literature available on different modalities, on interpatient registration and on different anatomical objects. Comparison studies including mutual information are also considered. The paper starts with a description of entropy and mutual information and it closes with a discussion on past achievements and some future challenges.
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Affiliation(s)
- Josien P W Pluim
- University Medical Center Utrecht, Image Sciences Institute, Room E01.335, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
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Fei B, Kemper C, Wilson DL. A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes. Comput Med Imaging Graph 2003; 27:267-81. [PMID: 12631511 DOI: 10.1016/s0895-6111(02)00093-9] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
A three-dimensional warping registration algorithm was created and compared to rigid body registration of magnetic resonance (MR) pelvic volumes including the prostate. The rigid body registration method combines the advantages of mutual information (MI) and correlation coefficient at different resolutions. Warping registration is based upon independent optimization of many interactively placed control points (CP's) using MI and a thin plate spline transformation. More than 100 registration experiments with 17 MR volume pairs determined the quality of registration under conditions simulating potential interventional MRI-guided treatments of prostate cancer. For image pairs that stress rigid body registration (e.g. supine, the diagnostic position, and legs raised, the treatment position), both visual and numerical evaluation methods showed that warping consistently worked better than rigid body. Experiments showed that approximately 180 strategically placed CP's were sufficiently expressive to capture important features of the deformation.
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Affiliation(s)
- Baowei Fei
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
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Lee Z, Nagano KK, Duerk JL, Sodee DB, Wilson DL. Automatic registration of MR and SPECT images for treatment planning in prostate cancer. Acad Radiol 2003; 10:673-84. [PMID: 12809423 DOI: 10.1016/s1076-6332(03)80088-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
RATIONALE AND OBJECTIVES To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate. MATERIALS AND METHODS The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2 degree difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists. RESULTS Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration. CONCLUSION Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.
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Affiliation(s)
- Zhenghong Lee
- Department of Radiology, University Hospitals of Cleveland, School of Medicine, Cleveland, Ohio 44106, USA
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Abstract
The ability to identify and characterize pulmonary nodules has been dramatically increased by the introduction of multislice CT (MSCT) technology. Using high-resolution sections, MSCT allows considerable improvement in assessing nodule morphology, enhancement patterns, and growth. MSCT also has facilitated the development and potential of clinical application of computer-assisted diagnosis.
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Affiliation(s)
- Jane P Ko
- Department of Radiology, New York University Medical Center, 560 1st Avenue, New York, NY 10016, USA.
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Heverhagen JT, Boehm D, Klose KJ. Calibrated magnetic resonance hydrometry: an in vitro study. J Magn Reson Imaging 2003; 17:472-7. [PMID: 12655587 DOI: 10.1002/jmri.10267] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
PURPOSE To demonstrate a quantitative approach to measuring fluid volumes with standard single shot RARE sequences. MATERIALS AND METHODS In phantom experiments, magnetic resonance hydrometry (MRH), in combination with various calibration phantoms (5 mL up to 500 mL) as internal standards, was used to quantify fluid volumes. In total, 16 volume phantoms were investigated with six different calibration phantoms. In addition, noise correction was implemented to correct the quantification results and to avoid the influence of random noise in the image. RESULTS All MR measurements show significant correlations of up to r = 0.99 (P <.05) with the real applied volume in the investigated phantoms. However, measurements of large volumes were more precise with large calibration phantoms. Noise reduction did not change the correlation between measured and real applied volumes, but did reduce the error of the measured volumes. Calibrated magnetic resonance hydrometry (cMRH) is able to quantify volumes of fluid fast and noninvasively. The volumes of the used calibration phantoms have to be at least in the order of magnitude of the volumes that are to be measured. CONCLUSION In vitro, cMRH using a single-shot rapid acquisition with refocused echoes (ssRARE) sequence and calibration phantoms is a fast and accurate method of quantifying steady amounts of fluid.
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Affiliation(s)
- Johannes T Heverhagen
- Department of Diagnostic Radiology, University Hospital, Philipps University, Marburg, Germany.
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