Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
A topology preserving level set method for geometric deformable models
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
Automated segmentation of cerebral aneurysms based on conditional random field and gentle adaboost
MeshMed'12 Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis
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We present an approach for accurate localization of the neck of intracranial aneurysms and quantification of their geometry that is useful for their treatment through endovascular embolization. In particular, we first obtain a vessel segmentation using a topology-preserving level set method and extract the surface of the segmented vessel. We then separate the aneurysm from the parent vessels and localize its neck by formulating the aneurysm segmentation problem as an s-t minimum cut problem. Finally, we estimate clinically relevant geometric parameters of the aneurysm. The results indicate that there is good agreement between the measurements obtained by the proposed approach and two independent manual sets of measurements obtained by two experienced interventional neuroradiologists.