Segmentation of lumen and outer wall of abdominal aortic aneurysms from 3D black-blood MRI with a registration based geodesic active contour model |
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| Institution: | 1. Radiology and Biomedical Imaging, University of California,San Francisco, San Francisco, United States;2. University of California, Berkeley; San Francisco, United States;3. Veterans Affairs Medical Center, San Francisco, United States;1. The University of Texas at San Antonio, Department of Biomedical Engineering, San Antonio, TX, USA;2. University of Navarra–Tecnun, Department of Mechanical Engineering, San Sebastian, Spain;3. The University of Texas at San Antonio, Department of Management Science and Statistics, San Antonio, TX, USA;4. Carnegie Mellon University, Department of Mechanical Engineering, Pittsburgh, PA, USA;5. Allegheny Health Network, Department of Thoracic and Cardiovascular Surgery, Pittsburgh, PA, USA;6. The University of Texas at San Antonio, Department of Mechanical Engineering, Room EB 3.04.08, One UTSA Circle, San Antonio, TX 78249, USA;1. IBIS Research Group, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain;2. Department of Computing Technology and Data Processing, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain;3. University Institute of Physics Applied to Sciences and Technologies, University of Alicante, Spain;4. Department Physics, Systems Engineering and Signal Theory, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain |
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| Abstract: | Segmentation of the geometric morphology of abdominal aortic aneurysm is important for interventional planning. However, the segmentation of both the lumen and the outer wall of aneurysm in magnetic resonance (MR) image remains challenging. This study proposes a registration based segmentation methodology for efficiently segmenting MR images of abdominal aortic aneurysms. The proposed methodology first registers the contrast enhanced MR angiography (CE-MRA) and black-blood MR images, and then uses the Hough transform and geometric active contours to extract the vessel lumen by delineating the inner vessel wall directly from the CE-MRA. The proposed registration based geometric active contour is applied to black-blood MR images to generate the outer wall contour. The inner and outer vessel wall are then fused presenting the complete vessel lumen and wall segmentation. The results obtained from 19 cases showed that the proposed registration based geometric active contour model was efficient and comparable to manual segmentation and provided a high segmentation accuracy with an average Dice value reaching 89.79%. |
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