Non-parametric geodesic active regions: Method and evaluation for cerebral aneurysms segmentation in 3DRA and CTA
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- 作者：Monica Hern ; ez ; Alej ; ro F. Frangi
- 关键词：Cerebral aneurysm ; Geodesic active regions ; Differential invariants ; Non-parametric probability estimation ; Model selection ; Evaluation
- 刊名：Medical Image Analysis
- 出版年：2007
- 出版时间：June 2007
- 年：2007
- 卷：11
- 期：3
- 页码：224-241
- 全文大小：1349 K
文摘
Segmentation of vascular structures is a difficult and challenging task. In this article, we present an algorithm devised for the segmentation of such structures. Our technique consists in a geometric deformable model with associated energy functional that incorporates high-order multiscale features in a non-parametric statistical framework. Although the proposed segmentation method is generic, it has been applied to the segmentation of cerebral aneurysms in 3DRA and CTA. An evaluation study over 10 clinical datasets indicate that the segmentations obtained by our method present a high overlap index with respect to the ground-truth (91.13 % and 73.31 % , respectively) and that the mean error distance from the surface to the ground truth is close to the in-plane resolution (0.40 and 0.38 mm, respectively). Besides, our technique favorably compares to other alternative techniques based on deformable models, namely parametric geodesic active regions and active contours without edges.