Title :
MS lesions segmentation in 3D MR images using FCM and SVM
Author :
Merzoug, Amina ; Benamrane, Nacera ; Ahmed, Abdelmalik Taleb
Author_Institution :
Dept. of Comput. Sci., USTO-MB, Oran, Algeria
Abstract :
This paper proposes an approach to automatically segment MS lesions in MR images using fuzzy c-means (FCM) and a support vector machines (SVM) based on the sequential minimal optimization (SMO) in learning step. A postprocessing based on morphological operations was applied to refine the obtained results. The proposed approach was tested on 3D MR images and the obtained results are encouraging.
Keywords :
biomedical MRI; fuzzy set theory; image segmentation; medical image processing; optimisation; support vector machines; 3D MR images; FCM; MS lesion segmentation; SVM; fuzzy c-means; morphological operations; sequential minimal optimization; support vector machines; Image segmentation; Lesions; Magnetic resonance imaging; Multiple sclerosis; Optimization; Support vector machines; Three-dimensional displays; 3D MR image; FCM; SMO; SVM; multiple sclerosis; segmentation;
Conference_Titel :
Image Processing Theory, Tools and Applications (IPTA), 2014 4th International Conference on
Conference_Location :
Paris
Print_ISBN :
978-1-4799-6462-8
DOI :
10.1109/IPTA.2014.7001924
