DocumentCode
1787186
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
fYear
2014
fDate
27-29 May 2014
Firstpage
189
Lastpage
192
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer-Based Medical Systems (CBMS), 2014 IEEE 27th International Symposium on
Conference_Location
New York, NY
Type
conf
DOI
10.1109/CBMS.2014.130
Filename
6881874
Link To Document