Title :
Automated segmentation of multiple sclerosis lesions using statistical approach
Author :
Sharma, Yamini ; Meghrajani, Yogesh K.
Author_Institution :
Dept. of Electron. & Commun., Dharmsinh Desai Univ., Nadiad, India
Abstract :
This paper describes a statistical approach for segmenting multiple sclerosis lesions (tumors) from magnetic resonance imaging (MRI) images. Proposed method detects and segments the areas inside the brain that are affected by tumors. Tumor regions are the areas of higher intensity in comparison to normal tissue. Our automated method gives satisfactory results showing that the proposed method is capable of segmenting multiple sclerosis lesions of different shapes and intensities. In order to show the efficacy of proposed approach, experimental results are compared with the results of other algorithm and also with the results of manual segmentation performed by experts.
Keywords :
biomedical MRI; brain; image segmentation; medical image processing; statistical analysis; tumours; MRI image; brain; magnetic resonance imaging; multiple sclerosis lesions automated segmentation; statistical approach; tumors; Gray-scale; Image reconstruction; Image segmentation; Lesions; Magnetic resonance imaging; Multiple sclerosis; MRI image; Multiple sclerosis (MS) lesions; intra - class variance; morphological operations; skull extraction;
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6817-6
DOI :
10.1109/ICIIECS.2015.7193144