Advanced algorithmic approaches to medical image segmentation
Statistical Study on Cortical Sulci of Human Brains
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
3D brain surface matching based on geodesics and local geometry
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Fast and accurate geodesic distance transform by ordered propagation
Image and Vision Computing
Double watermarks of 3D mesh model based on feature segmentation and redundancy information
Multimedia Tools and Applications
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The human cortical surface is a highly complex, folded structure. Cortical sulci, the spaces between the folds, define location on the cortex and provide a parcellation into functionally distinct areas. A topic that has recently received increased attention is the segmentation of these sulci from magnetic resonance (MR) images, with most work focusing on the extraction of the sulcal spaces between the folds. Unlike these methods, we propose a technique that extracts actual regions of the cortical surface that surround sulci, which we call 驴sulcal regions驴. The method is based on a watershed algorithm applied to a geodesic distance transform on the cortical surface. A well-known problem with the watershed algorithm is a tendency towards over segmentation. To address this problem, we propose a post-processing algorithm that merges appropriate segments from the watershed algorithm.