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Sahli H, Ben Slama A, Mouelhi A, Soayeh N, Rachdi R, Sayadi M. A computer-aided method based on geometrical texture features for a precocious detection of fetal Hydrocephalus in ultrasound images. Technol Health Care 2021; 28:643-664. [PMID: 32200362 DOI: 10.3233/thc-191752] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUD Hydrocephalus is the most common anomaly of the fetal head characterized by an excessive accumulation of fluid in the brain processing. The diagnostic process of fetal heads using traditional evaluation techniques are generally time consuming and error prone. Usually, fetal head size is computed using an ultrasound (US) image around 20-22 weeks, which is the gestational age (GA). Biometrical measurements are extracted and compared with ground truth charts to identify normal or abnormal growth. METHODS In this paper, an attempt has been made to enhance the Hydrocephalus characterization process by extracting other geometrical and textural features to design an efficient recognition system. The superiority of this work consists of the reduced time processing and the complexity of standard automatic approaches for routine examination. This proposed method requires practical insidiousness of the precocious discovery of fetuses' malformation to alert the experts about the existence of abnormal outcome. The first task is devoted to a proposed pre-processing model using a standard filtering and a segmentation scheme using a modified Hough transform (MHT) to detect the region of interest. Indeed, the obtained clinical parameters are presented to the principal component analysis (PCA) model in order to obtain a reduced number of measures which are employed in the classification stage. RESULTS Thanks to the combination of geometrical and statistical features, the classification process provided an important ability and an interesting performance achieving more than 96% of accuracy to detect pathological subjects in premature ages. CONCLUSIONS The experimental results illustrate the success and the accuracy of the proposed classification method for a factual diagnostic of fetal head malformation.
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Affiliation(s)
- Hanene Sahli
- University of Tunis, ENSIT, LR13ES03 SIME, Tunis, Tunisia
| | - Amine Ben Slama
- University of Tunis El Manar, ISTMT, LR13ES07, LRBTM, Tunis, Tunisia
| | - Aymen Mouelhi
- University of Tunis, ENSIT, LR13ES03 SIME, Tunis, Tunisia
| | - Nesrine Soayeh
- Obstetrics, Gynecology and Reproductive Department, Military Hospital, Tunis, Tunisia
| | - Radhouane Rachdi
- Obstetrics, Gynecology and Reproductive Department, Military Hospital, Tunis, Tunisia
| | - Mounir Sayadi
- University of Tunis, ENSIT, LR13ES03 SIME, Tunis, Tunisia
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Rajeswari J, Jagannath M. Advances in biomedical signal and image processing – A systematic review. INFORMATICS IN MEDICINE UNLOCKED 2017. [DOI: 10.1016/j.imu.2017.04.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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Rueda S, Knight CL, Papageorghiou AT, Noble JA. Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step. Med Image Anal 2015; 26:30-46. [PMID: 26319973 PMCID: PMC4686006 DOI: 10.1016/j.media.2015.07.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 05/28/2015] [Accepted: 07/11/2015] [Indexed: 11/24/2022]
Abstract
Medical ultrasound (US) image segmentation and quantification can be challenging due to signal dropouts, missing boundaries, and presence of speckle, which gives images of similar objects quite different appearance. Typically, purely intensity-based methods do not lead to a good segmentation of the structures of interest. Prior work has shown that local phase and feature asymmetry, derived from the monogenic signal, extract structural information from US images. This paper proposes a new US segmentation approach based on the fuzzy connectedness framework. The approach uses local phase and feature asymmetry to define a novel affinity function, which drives the segmentation algorithm, incorporates a shape-based object completion step, and regularises the result by mean curvature flow. To appreciate the accuracy and robustness of the methodology across clinical data of varying appearance and quality, a novel entropy-based quantitative image quality assessment of the different regions of interest is introduced. The new method is applied to 81 US images of the fetal arm acquired at multiple gestational ages, as a means to define a new automated image-based biomarker of fetal nutrition. Quantitative and qualitative evaluation shows that the segmentation method is comparable to manual delineations and robust across image qualities that are typical of clinical practice.
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Affiliation(s)
- Sylvia Rueda
- Centre of Excellence in Personalised Healthcare, Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, OX3 7DQ Oxford, UK.
| | - Caroline L Knight
- Centre of Excellence in Personalised Healthcare, Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, OX3 7DQ Oxford, UK; Nuffield Department of Obstetrics & Gynaecology, University of Oxford, Oxford, U.K
| | - Aris T Papageorghiou
- Nuffield Department of Obstetrics & Gynaecology, University of Oxford, Oxford, U.K; Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK
| | - J Alison Noble
- Centre of Excellence in Personalised Healthcare, Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Headington, OX3 7DQ Oxford, UK
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Hacihaliloglu I, Guy P, Hodgson AJ, Abugharbieh R. Automatic extraction of bone surfaces from 3D ultrasound images in orthopaedic trauma cases. Int J Comput Assist Radiol Surg 2015; 10:1279-87. [PMID: 25549799 DOI: 10.1007/s11548-014-1141-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2014] [Accepted: 12/16/2014] [Indexed: 10/24/2022]
Abstract
PURPOSE 3D ultrasound (US) imaging has the potential to become a powerful alternative imaging modality in orthopaedic surgery as it is radiation-free and can produce 3D images (in contrast to fluoroscopy) in near-real time. Conventional B-mode US images, however, are characterized by high levels of noise and reverberation artifacts, image quality is user-dependent, and bone surfaces are blurred, which makes it difficult to both interpret images and to use them as a basis for navigated interventions. 3D US has great potential to assist orthopaedic care, possibly assisting during surgery if the anatomical structures of interest could be localized and visualized with sufficient accuracy and clarity and in a highly automated rapid manner. METHODS In this paper, we present clinical results for a novel 3D US segmentation technique we have recently developed based on multi-resolution analysis to localize bone surfaces in 3D US volumes. Our method is validated on scans obtained from 29 trauma patients with distal radius and pelvic ring fractures. RESULTS Qualitative and quantitative results demonstrate remarkably clear segmentations of bone surfaces with an average surface fitting error of 0.62 mm (standard deviation (SD) of 0.42 mm) for pelvic patients and 0.21 mm (SD 0.14 mm) for distal radius patients. CONCLUSIONS These results suggest that our technique is sufficiently accurate for potential use in orthopaedic trauma applications.
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Affiliation(s)
- Ilker Hacihaliloglu
- Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, 08854, NJ, USA,
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Hacihaliloglu I, Rasoulian A, Rohling RN, Abolmaesumi P. Local phase tensor features for 3-D ultrasound to statistical shape+pose spine model registration. IEEE TRANSACTIONS ON MEDICAL IMAGING 2014; 33:2167-2179. [PMID: 24988590 DOI: 10.1109/tmi.2014.2332571] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Most conventional spine interventions are performed under X-ray fluoroscopy guidance. In recent years, there has been a growing interest to develop nonionizing imaging alternatives to guide these procedures. Ultrasound guidance has emerged as a leading alternative. However, a challenging problem is automatic identification of the spinal anatomy in ultrasound data. In this paper, we propose a local phase-based bone feature enhancement technique that can robustly identify the spine surface in ultrasound images. The local phase information is obtained using a gradient energy tensor filter. This information is used to construct local phase tensors in ultrasound images, which highlight the spine surface. We show that our proposed approach results in a more distinct enhancement of the bone surfaces compared to recently proposed techniques based on monogenic scale-space filters and logarithmic Gabor filters. We also demonstrate that registration accuracy of a statistical shape+pose model of the spine to 3-D ultrasound images can be significantly improved, using the proposed method, compared to those obtained using monogenic scale-space filters and logarithmic Gabor filters.
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Hacihaliloglu I, Guy P, Hodgson AJ, Abugharbieh R. Volume-specific parameter optimization of 3D local phase features for improved extraction of bone surfaces in ultrasound. Int J Med Robot 2014; 10:461-73. [DOI: 10.1002/rcs.1552] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2012] [Revised: 10/05/2013] [Accepted: 10/08/2013] [Indexed: 11/08/2022]
Affiliation(s)
- Ilker Hacihaliloglu
- Department of Orthopaedics; University of British Columbia; Vancouver BC Canada
| | - Pierre Guy
- Department of Orthopaedics; University of British Columbia; Vancouver BC Canada
| | - Antony J. Hodgson
- Department of Mechanical Engineering; University of British Columbia; Vancouver BC Canada
| | - Rafeef Abugharbieh
- Department of Electrical and Computer Engineering; University of British Columbia; Vancouver BC Canada
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Non-iterative partial view 3D ultrasound to CT registration in ultrasound-guided computer-assisted orthopedic surgery. Int J Comput Assist Radiol Surg 2012; 8:157-68. [DOI: 10.1007/s11548-012-0747-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2012] [Accepted: 05/03/2012] [Indexed: 10/28/2022]
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Hacihaliloglu I, Abugharbieh R, Hodgson AJ, Rohling RN, Guy P. Automatic bone localization and fracture detection from volumetric ultrasound images using 3-D local phase features. ULTRASOUND IN MEDICINE & BIOLOGY 2012; 38:128-144. [PMID: 22104523 DOI: 10.1016/j.ultrasmedbio.2011.10.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2011] [Revised: 09/05/2011] [Accepted: 10/13/2011] [Indexed: 05/31/2023]
Abstract
This article presents a novel method for bone segmentation from three-dimensional (3-D) ultrasound images that derives intensity-invariant 3-D local image phase measures that are then employed for extracting ridge-like features similar to those that occur at soft tissue/bone interfaces. The main contributions in this article include: (1) the extension of our previously proposed phase-symmetry-based bone surface extraction from two-dimensional (2-D) to 3-D images using 3-D Log-Gabor filters; (2) the design of a new framework for accuracy evaluation based on using computed tomography as a gold standard that allows the assessment of surface localization accuracy across the entire 3-D surface; (3) the quantitative validation of accuracy of our 3-D phase-processing approach on both intact and fractured bone surfaces using phantoms and ex vivo 3-D ultrasound scans; and (4) the qualitative validation obtained by scanning emergency room patients with distal radius and pelvis fractures. We show a 41% improvement in surface localization error over the previous 2-D phase symmetry method. The results demonstrate clearly visible segmentations of bone surfaces with a localization accuracy of <0.6 mm and mean errors in estimating fracture displacements below 0.6 mm. The results show that the proposed method is successful even for situations when the bone surface response is weak due to shadowing from muscle and fascia interfaces above the bone, which is a situation where the 2-D method fails.
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Affiliation(s)
- Ilker Hacihaliloglu
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
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Hacihaliloglu I, Abugharbieh R, Hodgson AJ, Rohling RN. Automatic adaptive parameterization in local phase feature-based bone segmentation in ultrasound. ULTRASOUND IN MEDICINE & BIOLOGY 2011; 37:1689-1703. [PMID: 21821346 DOI: 10.1016/j.ultrasmedbio.2011.06.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2010] [Revised: 06/02/2011] [Accepted: 06/14/2011] [Indexed: 05/31/2023]
Abstract
Intensity-invariant local phase features based on Log-Gabor filters have been recently shown to produce highly accurate localizations of bone surfaces from three-dimensional (3-D) ultrasound. A key challenge, however, remains in the proper selection of filter parameters, whose values have so far been chosen empirically and kept fixed for a given image. Since Log-Gabor filter responses widely change when varying the filter parameters, actual parameter selection can significantly affect the quality of extracted features. This article presents a novel method for contextual parameter selection that autonomously adapts to image content. Our technique automatically selects the scale, bandwidth and orientation parameters of Log-Gabor filters for optimizing local phase symmetry. The proposed approach incorporates principle curvature computed from the Hessian matrix and directional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro experiments demonstrate 35% improvement in accuracy of bone surface localization compared with empirically-set parameterization results. Results from a pilot in vivo study on human subjects, scanned in the operating room, show similar improvements.
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Affiliation(s)
- Ilker Hacihaliloglu
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
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Noble JA, Navab N, Becher H. Ultrasonic image analysis and image-guided interventions. Interface Focus 2011; 1:673-85. [PMID: 22866237 PMCID: PMC3262276 DOI: 10.1098/rsfs.2011.0025] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2011] [Accepted: 05/16/2011] [Indexed: 11/12/2022] Open
Abstract
The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.
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Affiliation(s)
- J. Alison Noble
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Nassir Navab
- Computer Aided Medical Procedures, Technische Universitat Munchen, Munchen, Germany
| | - H. Becher
- Mazankowski Alberta Heart Institute, University of Alberta Hospital, Alberta, Canada
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Belaid A, Boukerroui D, Maingourd Y, Lerallut JF. Phase-Based Level Set Segmentation of Ultrasound Images. ACTA ACUST UNITED AC 2011; 15:138-47. [PMID: 21216695 DOI: 10.1109/titb.2010.2090889] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Ahror Belaid
- Heudiasyc UMR CNRS 6599, Université de Technologie de Compiègne, Centre de Recherche de Royallieu, 60205 Compiègne Cedex, France.
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Hacihaliloglu I, Abugharbieh R, Hodgson AJ, Rohling RN. Bone surface localization in ultrasound using image phase-based features. ULTRASOUND IN MEDICINE & BIOLOGY 2009; 35:1475-87. [PMID: 19616363 DOI: 10.1016/j.ultrasmedbio.2009.04.015] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2008] [Revised: 04/01/2009] [Accepted: 04/18/2009] [Indexed: 05/24/2023]
Abstract
Current practice in orthopedic surgery relies on intraoperative fluoroscopy as the main imaging modality for localization and visualization of bone tissue, fractures, implants and surgical tool positions. Ultrasound (US) has recently emerged as a potential nonionizing imaging alternative that promises safer operation while remaining relatively cheap and widely available. US images, however, often depict bone structures poorly, making automatic, accurate and robust localization of bone surfaces quite challenging. In this paper, we present a novel technique for automatic bone surface localization in US that uses local phase image information to derive symmetry-based features corresponding to tissue/bone interfaces through the use of 2-D Log-Gabor filters. We validate the performance of the proposed approach quantitatively using realistic phantom and in vitro experiments as well as qualitatively on in vivo data. Results demonstrate that the proposed technique detects bone surfaces with a localization mean error below 0.40 mm. Furthermore, small gaps between bone fragments can be detected with fracture displacement mean error below 0.33 mm for vertical misalignments, and 0.47 mm for horizontal misalignments.
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Affiliation(s)
- Ilker Hacihaliloglu
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
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Noble JA, Boukerroui D. Ultrasound image segmentation: a survey. IEEE TRANSACTIONS ON MEDICAL IMAGING 2006; 25:987-1010. [PMID: 16894993 DOI: 10.1109/tmi.2006.877092] [Citation(s) in RCA: 306] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
This paper reviews ultrasound segmentation paper methods, in a broad sense, focusing on techniques developed for medical B-mode ultrasound images. First, we present a review of articles by clinical application to highlight the approaches that have been investigated and degree of validation that has been done in different clinical domains. Then, we present a classification of methodology in terms of use of prior information. We conclude by selecting ten papers which have presented original ideas that have demonstrated particular clinical usefulness or potential specific to the ultrasound segmentation problem.
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Affiliation(s)
- J Alison Noble
- Department of Engineering Science, University of Oxford, UK.
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Ye X, Noble JA, Atkinson D. 3-D freehand echocardiography for automatic left ventricle reconstruction and analysis based on multiple acoustic windows. IEEE TRANSACTIONS ON MEDICAL IMAGING 2002; 21:1051-1058. [PMID: 12564873 DOI: 10.1109/tmi.2002.804436] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
A new method is proposed to reconstruct and analyze the left ventricle (LV) from multiple acoustic window three-dimensional (3-D) ultrasound acquired using a transthoracic 3-D rotational probe. Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. A more extensive clinical validation is required to establish whether these promising first results translate to a method suitable for routine clinical use.
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Affiliation(s)
- Xujiong Ye
- Department of Engineering Science, University of Oxford, Parks Road, OX1 3PJ Oxford, UK.
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Sanchez-Ortiz GI, Wright GJT, Clarke N, Declerck J, Banning AP, Noble JA. Automated 3-D echocardiography analysis compared with manual delineations and SPECT MUGA. IEEE TRANSACTIONS ON MEDICAL IMAGING 2002; 21:1069-1076. [PMID: 12564875 DOI: 10.1109/tmi.2002.804434] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
A major barrier for using 3-D echocardiography for quantitative analysis of heart function in routine clinical practice is the absence of accurate and robust segmentation and tracking methods necessary to make the analysis automatic. In this paper, we present an automated three-dimensional (3-D) echocardiographic acquisition and image-processing methodology for assessment of left ventricular (LV) function. We combine global image information provided by a novel multiscale fuzzy-clustering segmentation algorithm, with local boundaries obtained with phase-based acoustic feature detection. We then use the segmentation results to fit and track the LV endocardial surface using a 3-D continuous transformation. To our knowledge, this is the first report of a completely automated method. The protocol is evaluated in a small clinical case study (nine patients). We compare ejection fractions (EFs) computed with the new approach to those obtained using the standard clinical technique, single-photon emission computed tomography multigated acquisition. Errors on six datasets were found to be within six percentage points. A further two, with poor image quality, improved upon EFs from manually delineated contours, and the last failed due to artifacts in the data. Volume-time curves were derived and the results compared to those from manual segmentation. Improvement over an earlier published version of the method is noted.
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