DocumentCode
156388
Title
Brief review of multiple sclerosis lesions segmentation methods on conventional magnetic resonance imaging
Author
Ghribi, Olfa ; Njeh, Ines ; Ben Hamida, Ahmed ; Zouch, Wassim ; Mhiri, Chokri
Author_Institution
ENIS, Sfax Univ., Sfax, Tunisia
fYear
2014
fDate
17-19 March 2014
Firstpage
249
Lastpage
253
Abstract
Multiple sclerosis is a chronic inflammatory disease of the central nervous system. Lesions detected by Magnetic resonance (MR) sequences not only confirme the diagnosis of MS, but let monitor them to determine the evolutionary state of the disease and to evaluate the therapeutic efficiency. Thus, the change in lesion load is a criterion determining the degree of progress of the disease in volume, shape and location. For this purpose, a segmentation of these lesions becomes paramount. Some recent methods of semiautomatic and automatic segmentation have been proposed to get rid of complex and laborious manual segmentation. Subsequently, the variability inter and intra-experts will be reduced. The purpose of this study is to accomplish a brief review of MS lesions segmentation methods proposed in the literature.
Keywords
biological tissues; biomedical MRI; diseases; image segmentation; medical image processing; neurophysiology; patient monitoring; MR sequences; MS diagnosis; central nervous system; chronic inflammatory disease; conventional magnetic resonance imaging; disease evolutionary state determination; disease progress; inter-expert variability reduction; intra-expert variability reduction; lesion detection; lesion load change; lesion location; lesion monitoring; lesion shape; lesion volume; manual segmentation; multiple sclerosis lesion segmentation methods; review; semiautomatic segmentation; therapeutic efficiency evaluation; Image segmentation; Lesions; Magnetic resonance imaging; Manuals; Multiple sclerosis; Shape; Automatic segmentation; Lesions segmentation; MRI; Multiple sclerosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Technologies for Signal and Image Processing (ATSIP), 2014 1st International Conference on
Conference_Location
Sousse
Type
conf
DOI
10.1109/ATSIP.2014.6834616
Filename
6834616
Link To Document