Improving Deformable Surface Meshes through Omni-Directional Displacements and MRFs
暂无分享,去创建一个
[1] Stefan Zachow,et al. Automatic Extraction of Mandibular Nerve and Bone from Cone-Beam CT Data , 2009, MICCAI.
[2] Timothy F. Cootes,et al. Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..
[3] Demetri Terzopoulos,et al. Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..
[4] Myoung-Hee Kim,et al. A non-self-intersecting adaptive deformable surface for complex boundary extraction from volumetric images , 2001, Comput. Graph..
[5] Johan Montagnat,et al. A review of deformable surfaces: topology, geometry and deformation , 2001, Image Vis. Comput..
[6] Thomas Lange,et al. Shape Constrained Automatic Segmentation of the Liver based on a Heuristic Intensity Model , 2007 .
[7] Hans-Christian Hege,et al. Automatic Segmentation of the Pelvic Bones from CT Data Based on a Statistical Shape Model , 2008, VCBM.
[8] Christopher J. Taylor,et al. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009 , 2009, Lecture Notes in Computer Science.
[9] Nikos Komodakis,et al. Performance vs computational efficiency for optimizing single and dynamic MRFs: Setting the state of the art with primal-dual strategies , 2008, Comput. Vis. Image Underst..
[10] Xiaodong Wu,et al. Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Nassir Navab,et al. Dense image registration through MRFs and efficient linear programming , 2008, Medical Image Anal..