Title :
An Information Theoretic Approach via IJM to Segmenting MR Images with MS Lesions
Author :
Hill, Jason E. ; Nutter, Brian ; Mitra, Subhasish
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Tech Univ., Lubbock, TX, USA
Abstract :
Automated detection of brain pathologies from Magnetic Resonance (MR) images remains an outstanding problem. An information theoretic approach for automated segmentation of medical images called the Improved "Jump" Method (IJM) has been recently developed and validated. Here we extend this work by utilizing IJM to segment human brain MR images with multiple-sclerosis (MS) lesions in order to probe IJM\´s limitations and versatility.
Keywords :
biomedical MRI; brain; diseases; image segmentation; information theory; IJM; MR image segmentation; MS lesions; automated brain pathology detection; automated medical image segmentation; improved jump method; information theory; magnetic resonance images; multiple-sclerosis lesions; Accuracy; Biomedical imaging; Histograms; Image segmentation; Kernel; Lesions; Magnetic resonance imaging; information theory; model order estimation; segmentation;
Conference_Titel :
Computer-Based Medical Systems (CBMS), 2014 IEEE 27th International Symposium on
Conference_Location :
New York, NY
DOI :
10.1109/CBMS.2014.130
