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Segmentation of Lumen and Outer wall of Abdominal Aortic Aneurysms from 3D Black-Blood MRI with a Registration Based Geodesic Active Contour Model

机译：基于配准测地线活动轮廓模型的3D黑血MRI分割腹主动脉瘤腔和外壁

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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%.
机译：腹主动脉瘤的几何形态分割对于介入计划很重要。然而，在磁共振（MR）图像中对动脉瘤的内腔和外壁的分割仍然具有挑战性。这项研究提出了一种基于注册的分割方法，可以有效地分割腹主动脉瘤的MR图像。所提出的方法首先记录对比增强MR血管造影（CE-MRA）和黑血MR图像，然后使用Hough变换和几何有效轮廓通过直接从CE-MRA描绘血管内壁来提取血管腔。所提出的基于配准的几何有效轮廓被应用于黑MR图像以生成外壁轮廓。然后融合内部和外部血管壁，呈现完整的血管内腔和壁分割。从19个案例中获得的结果表明，所提出的基于配准的几何有效轮廓模型是有效的，并且可以与手动分割相媲美，并且具有很高的分割精度，平均Dice值达到89.79％。

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