title: [Segmentation of multiple sclerosis lesions based on Markov random fields model for MR images].
abstract: Multiple sclerosis (MS) is an inflammatory demyelinating disease that would damage central nervous system. There is a growing attention to the segmentation algorithms of MS Lesions. An MRF-based algorithm for MS lesions segmentation of T2-weighted MR brain images is developed by utilizing the morphological characteristics of MS lesion tissues. The regions circumscribed by white matter are extracted at first by MRF-based segmentation and region growing methods; the abstracted regions are then segmented again using MRF-based algorithm. The segmented MS lesions of both simulated and clinical T2-weighted MR brain images are presented in the current work. The testing results show that the proposed algorithm is robust and accurate enough for clinical use.
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Li
authors.forename: Wufan
authors.initials: W
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008390:Markov Chains; D009103:Multiple Sclerosis / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods