1
|
Dabus G, Kotecha R, Linfante I, Wieczorek DJ, Gutierrez AN, Candela JG, McDermott MW. Analysis of potential time saving in brain arteriovenous malformation stereotactic radiosurgery planning using a new software platform. Med Dosim 2021; 47:38-42. [PMID: 34481717 DOI: 10.1016/j.meddos.2021.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 05/31/2021] [Accepted: 07/24/2021] [Indexed: 11/15/2022]
Abstract
To evaluate the utility of integrating a 3D vessel tree co-registration software platform into the stereotactic radiosurgery (SRS) workflow and its time saving for brain arteriovenous malformation (bAVM) treatment in adults compared to the conventional stereotactic head frame workflow. Eight consecutive adult bAVM cases were selected and retrospectively reviewed. Total number of angiograms and SRS procedures were 8. The electronic medical records were analyzed by time stamps to determine the length of time for each component of the set-up, transport, and frame removal. Times were averaged and the start of sedation by anesthesia used as a surrogate for the start of the frame application process. Reductions in workflow times were then modeled assuming cerebral angiography as a separate procedure. There were 8 adult bAVM cases included. Six were female. All patients had a single treatment session. Average age was 51.5 years (Range: 36-71). All patients were treated under monitored anesthesia care. In 6 patients, the AVM was deeply located (basal ganglia, midbrain, brainstem); in 2 cases, the lesion was frontal. Spetzler-Martin grades were 4 (50%) Grade 2 and 4 (50%) Grade 3. The average prescription isodose volume (PIV) and 12 Gy volumes (V12Gy) were 0.85 cc and 1.74 cc, respectively. The mean time from frame application to arrival in the angiography room was 111.5 minutes (range 40 to 171 min; median 107 min; SD 35.3 min); transport from angiography room to SRS was 47.5 minutes (range 15 to 107 min; median 36 min; SD 31.1 min), and frame removal after SRS was 20.5 minutes (range 10 to 47 min; median 16 min; SD 11.6 min). The average total additional time for the entire process of frame application, patient transportation, and frame removal was 132 minutes (range 87 to 181 min; median 127.5 min; SD 28.4 min). Therefore, assuming a non-frame based workflow and with angiography performed ahead of the actual radiosurgical treatment, the total time savings on the day of treatment was estimated at 132 minutes (range 87 to 181 min; median 127.5 min; SD 28.4 min). The ability to perform angiography, image fusion, and treatment planning for the actual day-of-delivery using 3-dimensional vessel tree co-registration could result in significant time savings over traditional workflow practices. Further experience with this system will evaluate its accuracy, reproducibility, and potential broader use in SRS workflow paradigms for the treatment of vascular pathologies. For bAVMs, the benefits of this time savings might allow for streamlined workflows on the day of SRS.
Collapse
Affiliation(s)
- Guilherme Dabus
- Miami Neuroscience Institute, Baptist Health South Florida, Miami, FL; Miami Cardiac & Vascular Institute, Baptist Health South Florida, Miami, FL; Herbert Wertheim College of Medicine, Florida International University, Miami, FL.
| | - Rupesh Kotecha
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL; Herbert Wertheim College of Medicine, Florida International University, Miami, FL
| | - Italo Linfante
- Miami Neuroscience Institute, Baptist Health South Florida, Miami, FL; Miami Cardiac & Vascular Institute, Baptist Health South Florida, Miami, FL; Herbert Wertheim College of Medicine, Florida International University, Miami, FL
| | - D Jay Wieczorek
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL; Herbert Wertheim College of Medicine, Florida International University, Miami, FL
| | - Alonso N Gutierrez
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL; Herbert Wertheim College of Medicine, Florida International University, Miami, FL
| | - John G Candela
- Miami Neuroscience Institute, Baptist Health South Florida, Miami, FL
| | - Michael W McDermott
- Miami Neuroscience Institute, Baptist Health South Florida, Miami, FL; Herbert Wertheim College of Medicine, Florida International University, Miami, FL
| |
Collapse
|
2
|
Mitrović U, Pernuš F, Likar B, Špiclin Ž. Simultaneous 3D-2D image registration and C-arm calibration: Application to endovascular image-guided interventions. Med Phys 2016; 42:6433-47. [PMID: 26520733 DOI: 10.1118/1.4932626] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Three-dimensional to two-dimensional (3D-2D) image registration is a key to fusion and simultaneous visualization of valuable information contained in 3D pre-interventional and 2D intra-interventional images with the final goal of image guidance of a procedure. In this paper, the authors focus on 3D-2D image registration within the context of intracranial endovascular image-guided interventions (EIGIs), where the 3D and 2D images are generally acquired with the same C-arm system. The accuracy and robustness of any 3D-2D registration method, to be used in a clinical setting, is influenced by (1) the method itself, (2) uncertainty of initial pose of the 3D image from which registration starts, (3) uncertainty of C-arm's geometry and pose, and (4) the number of 2D intra-interventional images used for registration, which is generally one and at most two. The study of these influences requires rigorous and objective validation of any 3D-2D registration method against a highly accurate reference or "gold standard" registration, performed on clinical image datasets acquired in the context of the intervention. METHODS The registration process is split into two sequential, i.e., initial and final, registration stages. The initial stage is either machine-based or template matching. The latter aims to reduce possibly large in-plane translation errors by matching a projection of the 3D vessel model and 2D image. In the final registration stage, four state-of-the-art intrinsic image-based 3D-2D registration methods, which involve simultaneous refinement of rigid-body and C-arm parameters, are evaluated. For objective validation, the authors acquired an image database of 15 patients undergoing cerebral EIGI, for which accurate gold standard registrations were established by fiducial marker coregistration. RESULTS Based on target registration error, the obtained success rates of 3D to a single 2D image registration after initial machine-based and template matching and final registration involving C-arm calibration were 36%, 73%, and 93%, respectively, while registration accuracy of 0.59 mm was the best after final registration. By compensating in-plane translation errors by initial template matching, the success rates achieved after the final stage improved consistently for all methods, especially if C-arm calibration was performed simultaneously with the 3D-2D image registration. CONCLUSIONS Because the tested methods perform simultaneous C-arm calibration and 3D-2D registration based solely on anatomical information, they have a high potential for automation and thus for an immediate integration into current interventional workflow. One of the authors' main contributions is also comprehensive and representative validation performed under realistic conditions as encountered during cerebral EIGI.
Collapse
Affiliation(s)
- Uroš Mitrović
- Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, Ljubljana 1000, Slovenia and Cosylab, Control System Laboratory, Teslova ulica 30, Ljubljana 1000, Slovenia
| | - Franjo Pernuš
- Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, Ljubljana 1000, Slovenia
| | - Boštjan Likar
- Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, Ljubljana 1000, Slovenia and Sensum, Computer Vision Systems, Tehnološki Park 21, Ljubljana 1000, Slovenia
| | - Žiga Špiclin
- Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, Ljubljana 1000, Slovenia and Sensum, Computer Vision Systems, Tehnološki Park 21, Ljubljana 1000, Slovenia
| |
Collapse
|
3
|
Yeom E, Nam KH, Jin C, Paeng DG, Lee SJ. 3D reconstruction of a carotid bifurcation from 2D transversal ultrasound images. ULTRASONICS 2014; 54:2184-2192. [PMID: 24965564 DOI: 10.1016/j.ultras.2014.06.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Revised: 05/12/2014] [Accepted: 06/01/2014] [Indexed: 06/03/2023]
Abstract
Visualizing and analyzing the morphological structure of carotid bifurcations are important for understanding the etiology of carotid atherosclerosis, which is a major cause of stroke and transient ischemic attack. For delineation of vasculatures in the carotid artery, ultrasound examinations have been widely employed because of a noninvasive procedure without ionizing radiation. However, conventional 2D ultrasound imaging has technical limitations in observing the complicated 3D shapes and asymmetric vasodilation of bifurcations. This study aims to propose image-processing techniques for better 3D reconstruction of a carotid bifurcation in a rat by using 2D cross-sectional ultrasound images. A high-resolution ultrasound imaging system with a probe centered at 40MHz was employed to obtain 2D transversal images. The lumen boundaries in each transverse ultrasound image were detected by using three different techniques; an ellipse-fitting, a correlation mapping to visualize the decorrelation of blood flow, and the ellipse-fitting on the correlation map. When the results are compared, the third technique provides relatively good boundary extraction. The incomplete boundaries of arterial lumen caused by acoustic artifacts are somewhat resolved by adopting the correlation mapping and the distortion in the boundary detection near the bifurcation apex was largely reduced by using the ellipse-fitting technique. The 3D lumen geometry of a carotid artery was obtained by volumetric rendering of several 2D slices. For the 3D vasodilatation of the carotid bifurcation, lumen geometries at the contraction and expansion states were simultaneously depicted at various view angles. The present 3D reconstruction methods would be useful for efficient extraction and construction of the 3D lumen geometries of carotid bifurcations from 2D ultrasound images.
Collapse
Affiliation(s)
- Eunseop Yeom
- Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, South Korea
| | - Kweon-Ho Nam
- Department of Ocean System Engineering, Interdisciplinary Postgraduate Program in Biomedical Engineering, Jeju National University, Jeju, South Korea
| | - Changzhu Jin
- Department of Ocean System Engineering, Interdisciplinary Postgraduate Program in Biomedical Engineering, Jeju National University, Jeju, South Korea
| | - Dong-Guk Paeng
- Department of Ocean System Engineering, Interdisciplinary Postgraduate Program in Biomedical Engineering, Jeju National University, Jeju, South Korea.
| | - Sang-Joon Lee
- Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, South Korea.
| |
Collapse
|
4
|
Flach B, Brehm M, Sawall S, Kachelrieß M. Deformable 3D–2D registration for CT and its application to low dose tomographic fluoroscopy. Phys Med Biol 2014; 59:7865-87. [DOI: 10.1088/0031-9155/59/24/7865] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
5
|
Mitrovic U, Špiclin Ž, Likar B, Pernuš F. 3D-2D registration of cerebral angiograms: a method and evaluation on clinical images. IEEE TRANSACTIONS ON MEDICAL IMAGING 2013; 32:1550-1563. [PMID: 23649179 DOI: 10.1109/tmi.2013.2259844] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established "gold standard" registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI.
Collapse
Affiliation(s)
- Uroš Mitrovic
- Faculty of Electrical Engineering, University of Ljubljana, SI-1000 Ljubljana, Slovenia.
| | | | | | | |
Collapse
|
6
|
Forkert ND, Fiehler J, Illies T, Möller DPF, Handels H, Säring D. 4D blood flow visualization fusing 3D and 4D MRA image sequences. J Magn Reson Imaging 2012; 36:443-53. [PMID: 22535682 DOI: 10.1002/jmri.23652] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2011] [Accepted: 02/29/2012] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To present and evaluate the feasibility of a novel automatic method for generating 4D blood flow visualizations fusing high spatial resolution 3D and time-resolved (4D) magnetic resonance angiography (MRA) datasets. MATERIALS AND METHODS In a first step, the cerebrovascular system is segmented in the 3D MRA dataset and a surface model is computed. The hemodynamic information is extracted from the 4D MRA dataset and transferred to the surface model using rigid registration where it can be visualized color-coded or dynamically over time. The presented method was evaluated using software phantoms and 20 clinical datasets from patients with an arteriovenous malformation. Clinical evaluation was performed by comparison of Spetzler-Martin scores determined from the 4D blood flow visualizations and corresponding digital subtraction angiographies. RESULTS The performed software phantom validation showed that the presented method is capable of producing reliable visualization results for vessels with a minimum diameter of 2 mm for which a mean temporal error of 0.27 seconds was achieved. The clinical evaluation based on 20 datasets comparing the 4D visualization to DSA images revealed an excellent interrater reliability. CONCLUSION The presented method enables an improved combined representation of blood flow and anatomy while reducing the time needed for clinical rating.
Collapse
Affiliation(s)
- Nils Daniel Forkert
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany.
| | | | | | | | | | | |
Collapse
|
7
|
Markelj P, Tomaževič D, Likar B, Pernuš F. A review of 3D/2D registration methods for image-guided interventions. Med Image Anal 2012; 16:642-61. [PMID: 20452269 DOI: 10.1016/j.media.2010.03.005] [Citation(s) in RCA: 328] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2009] [Revised: 02/22/2010] [Accepted: 03/30/2010] [Indexed: 02/07/2023]
|
8
|
Ruijters D, Homan R, Mielekamp P, van de Haar P, Babic D. Validation of 3D multimodality roadmapping in interventional neuroradiology. Phys Med Biol 2011; 56:5335-54. [PMID: 21799235 DOI: 10.1088/0031-9155/56/16/017] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Three-dimensional multimodality roadmapping is entering clinical routine utilization for neuro-vascular treatment. Its purpose is to navigate intra-arterial and intra-venous endovascular devices through complex vascular anatomy by fusing pre-operative computed tomography (CT) or magnetic resonance (MR) with the live fluoroscopy image. The fused image presents the real-time position of the intra-vascular devices together with the patient's 3D vascular morphology and its soft-tissue context. This paper investigates the effectiveness, accuracy, robustness and computation times of the described methods in order to assess their suitability for the intended clinical purpose: accurate interventional navigation. The mutual information-based 3D-3D registration proved to be of sub-voxel accuracy and yielded an average registration error of 0.515 mm and the live machine-based 2D-3D registration delivered an average error of less than 0.2 mm. The capture range of the image-based 3D-3D registration was investigated to characterize its robustness, and yielded an extent of 35 mm and 25° for >80% of the datasets for registration of 3D rotational angiography (3DRA) with CT, and 15 mm and 20° for >80% of the datasets for registration of 3DRA with MR data. The image-based 3D-3D registration could be computed within 8 s, while applying the machine-based 2D-3D registration only took 1.5 µs, which makes them very suitable for interventional use.
Collapse
Affiliation(s)
- Daniel Ruijters
- Interventional X-Ray (iXR), Philips Healthcare, Best, The Netherlands.
| | | | | | | | | |
Collapse
|
9
|
A comparative study on manual and automatic slice-to-volume registration of CT images. Eur Radiol 2009; 19:2647-53. [PMID: 19504108 DOI: 10.1007/s00330-009-1452-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2008] [Accepted: 04/16/2009] [Indexed: 10/20/2022]
Abstract
In order to assess the clinical relevance of a slice-to-volume registration algorithm, this technique was compared to manual registration. Reformatted images obtained from a diagnostic CT examination of the lower abdomen were reviewed and manually registered by 41 individuals. The results were refined by the algorithm. Furthermore, a fully automatic registration of the single slices to the whole CT examination, without manual initialization, was also performed. The manual registration error for rotation and translation was found to be 2.7+/-2.8 degrees and 4.0+/-2.5 mm. The automated registration algorithm significantly reduced the registration error to 1.6+/-2.6 degrees and 1.3+/-1.6 mm (p = 0.01). In 3 of 41 (7.3%) registration cases, the automated registration algorithm failed completely. On average, the time required for manual registration was 213+/-197 s; automatic registration took 82+/-15 s. Registration was also performed without any human interaction. The resulting registration error of the algorithm without manual pre-registration was found to be 2.9+/-2.9 degrees and 1.1+/-0.2 mm. Here, a registration took 91+/-6 s, on average. Overall, the automated registration algorithm improved the accuracy of manual registration by 59% in rotation and 325% in translation. The absolute values are well within a clinically relevant range.
Collapse
|
10
|
Strobel N, Meissner O, Boese J, Brunner T, Heigl B, Hoheisel M, Lauritsch G, Nagel M, Pfister M, Rührnschopf EP, Scholz B, Schreiber B, Spahn M, Zellerhoff M, Klingenbeck-Regn K. 3D Imaging with Flat-Detector C-Arm Systems. MULTISLICE CT 2008. [DOI: 10.1007/978-3-540-33125-4_3] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
|
11
|
Penney GP, Edwards PJ, Hipwell JH, Slomczykowski M, Revie I, Hawkes DJ. Postoperative Calculation of Acetabular Cup Position Using 2-D–3-D Registration. IEEE Trans Biomed Eng 2007; 54:1342-8. [PMID: 17605366 DOI: 10.1109/tbme.2007.890737] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
A method to accurately measure the position and orientation of an acetabular cup implant from postoperative X-rays has been designed and validated. The method uses 2-D-3-D registration to align both the prosthesis and the preoperative computed tomography (CT) volume to the X-ray image. This allows the position of the implant to be calculated with respect to a CT-based surgical plan. Experiments have been carried out using ten sets of patient data. A conventional plain-film measurement technique was also investigated. A gold standard implant position and orientation was calculated using postoperative CT. Results show our method to be significantly more accurate than the plain-film method for calculating cup anteversion. Cup orientation and position could be measured to within a mean absolute error of 1.4 mm or degrees.
Collapse
Affiliation(s)
- Graeme P Penney
- Imaging Sciences Division, Guy's King's and St Thomas' Schools of Medicine, Kings College London, London SEI 3RB, UK.
| | | | | | | | | | | |
Collapse
|
12
|
Gorges S, Kerrien E, Berger MO, Trousset Y, Pescatore J, Anxionnat R, Picard L. Model of a vascular C-arm for 3D augmented fluoroscopy in interventional radiology. ACTA ACUST UNITED AC 2006; 8:214-22. [PMID: 16685962 DOI: 10.1007/11566489_27] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
This paper deals with the modeling of a vascular C-arm to generate 3D augmented fluoroscopic images in an interventional radiology context. A methodology based on the use of a multi-image calibration is proposed to assess the physical behavior of the C-arm. From the knowledge of the main characteristics of the C-arm, realistic models of the acquisition geometry are proposed. Their accuracy was evaluated and experiments showed that the C-arm geometry can be predicted with a mean 2D reprojection error of 0.5 mm. The interest of 3D augmented fluoroscopy is also assessed on a clinical case.
Collapse
|
13
|
Turgeon GA, Lehmann G, Guiraudon G, Drangova M, Holdsworth D, Peters T. 2D-3D registration of coronary angiograms for cardiac procedure planning and guidance. Med Phys 2006; 32:3737-49. [PMID: 16475773 DOI: 10.1118/1.2123350] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
We present a completely automated 2D-3D registration technique that accurately maps a patient-specific heart model, created from preoperative images, to the patient's orientation in the operating room. This mapping is based on the registration of preoperatively acquired 3D vascular data with intraoperatively acquired angiograms. Registration using both single and dual-plane angiograms is explored using simulated but realistic datasets that were created from clinical images. Heart deformations and cardiac phase mismatches are taken into account in our validation using a digital 4D human heart model. In an ideal situation where the pre- and intraoperative images were acquired at identical time points within the cardiac cycle, the single-plane and the dual-plane registrations resulted in 3D root-mean-square (rms) errors of 1.60 +/- 0.21 and 0.53 +/- 0.08 mm, respectively. When a 10% timing offset was added between the pre- and the intraoperative acquisitions, the single-plane registration approach resulted in inaccurate registrations in the out-of-plane axis, whereas the dual-plane registration exhibited a 98% success rate with a 3D rms error of 1.33 +/- 0.28 mm. When all potential sources of error were included, namely, the anatomical background, timing offset, and typical errors in the vascular tree reconstruction, the dual-plane registration performed at 94% with an accuracy of 2.19 +/- 0.77 mm.
Collapse
Affiliation(s)
- Guy-Anne Turgeon
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | | | | | | | | | | |
Collapse
|
14
|
van de Kraats EB, Penney GP, Tomazevic D, van Walsum T, Niessen WJ. Standardized evaluation methodology for 2-D-3-D registration. IEEE TRANSACTIONS ON MEDICAL IMAGING 2005; 24:1177-89. [PMID: 16156355 DOI: 10.1109/tmi.2005.853240] [Citation(s) in RCA: 90] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
In the past few years, a number of two-dimensional (2-D) to three-dimensional (3-D) (2-D-3-D) registration algorithms have been introduced. However, these methods have been developed and evaluated for specific applications, and have not been directly compared. Understanding and evaluating their performance is therefore an open and important issue. To address this challenge we introduce a standardized evaluation methodology, which can be used for all types of 2-D-3-D registration methods and for different applications and anatomies. Our evaluation methodology uses the calibrated geometry of a 3-D rotational X-ray (3DRX) imaging system (Philips Medical Systems, Best, The Netherlands) in combination with image-based 3-D-3-D registration for attaining a highly accurate gold standard for 2-D X-ray to 3-D MR/CT/3DRX registration. Furthermore, we propose standardized starting positions and failure criteria to allow future researchers to directly compare their methods. As an illustration, the proposed methodology has been used to evaluate the performance of two 2-D-3-D registration techniques, viz. a gradient-based and an intensity-based method, for images of the spine. The data and gold standard transformations are available on the internet (http://www.isi.uu.nl/Research/Databases/).
Collapse
Affiliation(s)
- Everine B van de Kraats
- Image Sciences Institute, University Medical Center Utrecht, room QOS.459, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
| | | | | | | | | |
Collapse
|
15
|
Birkfellner W, Seemann R, Figl M, Hummel J, Ede C, Homolka P, Yang X, Niederer P, Bergmann H. Wobbled splatting—a fast perspective volume rendering method for simulation of x-ray images from CT. Phys Med Biol 2005; 50:N73-84. [PMID: 15843725 DOI: 10.1088/0031-9155/50/9/n01] [Citation(s) in RCA: 53] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
3D/2D registration, the automatic assignment of a global rigid-body transformation matching the coordinate systems of patient and preoperative volume scan using projection images, is an important topic in image-guided therapy and radiation oncology. A crucial part of most 3D/2D registration algorithms is the fast computation of digitally rendered radiographs (DRRs) to be compared iteratively to radiographs or portal images. Since registration is an iterative process, fast generation of DRRs-which are perspective summed voxel renderings-is desired. In this note, we present a simple and rapid method for generation of DRRs based on splat rendering. As opposed to conventional splatting, antialiasing of the resulting images is not achieved by means of computing a discrete point spread function (a so-called footprint), but by stochastic distortion of either the voxel positions in the volume scan or by the simulation of a focal spot of the x-ray tube with non-zero diameter. Our method generates slightly blurred DRRs suitable for registration purposes at framerates of approximately 10 Hz when rendering volume images with a size of 30 MB.
Collapse
Affiliation(s)
- Wolfgang Birkfellner
- Center for Biomedical Engineering and Physics, Medical University Vienna, Vienna, Austria
| | | | | | | | | | | | | | | | | |
Collapse
|
16
|
Registration of 3D Angiographic and X-Ray Images Using Sequential Monte Carlo Sampling. ACTA ACUST UNITED AC 2005. [DOI: 10.1007/11569541_43] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
|
17
|
Hawkes DJ, Barratt D, Blackall JM, Chan C, Edwards PJ, Rhode K, Penney GP, McClelland J, Hill DLG. Tissue deformation and shape models in image-guided interventions: a discussion paper. Med Image Anal 2004; 9:163-75. [PMID: 15721231 DOI: 10.1016/j.media.2004.11.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
This paper promotes the concept of active models in image-guided interventions. We outline the limitations of the rigid body assumption in image-guided interventions and describe how intraoperative imaging provides a rich source of information on spatial location of anatomical structures and therapy devices, allowing a preoperative plan to be updated during an intervention. Soft tissue deformation and variation from an atlas to a particular individual can both be determined using non-rigid registration. Established methods using free-form deformations have a very large number of degrees of freedom. Three examples of deformable models--motion models, biomechanical models and statistical shape models--are used to illustrate how prior information can be used to restrict the number of degrees of freedom of the registration algorithm and thus provide active models for image-guided interventions. We provide preliminary results from applications for each type of model.
Collapse
Affiliation(s)
- D J Hawkes
- Division of Imaging Sciences, GKT School of Medicine, King's College London, UK.
| | | | | | | | | | | | | | | | | |
Collapse
|
18
|
|