3D Symmetry Detection Using The Extended Gaussian Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accurate Robust Symmetry Estimation
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Robust Midsagittal Plane Extraction from Coarse, Pathological 3D Images
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Visualising Cerebral Asymmetry
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Shape Bottlenecks and Conservative Flow Systems
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Shape Analysis of Human Brain Interhemispheric Fissure Bending in MRI
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
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Current automatic methods based on mid-sagittal plane to segment left and right human brain hemispheres in 3D magnetic resonance (MR) images simply use a planar surface. However, the two brain hemispheres, in fact, can not be separated by just a simple plane properly. A novel automatic method to segment left and right brain hemispheres in MR images is proposed in this paper, which is based on an extended shape bottlenecks algorithm and a fast and robust partial volume estimation approach. In this method, brain tissues firstly are extracted from the MR image of human head. Then the information potential map is generated, according to which a brain hemisphere mask with the same size of the original image is created. 10 simulated and 5 real T1-weighted MR images were used to evaluate this method, and much more accurate segmentation of human brain hemispheres was achieved comparing with the segmentation with mid-sagittal plane.