Title: Analysis of hippocampus in multiple sclerosis-associated depression using image processing
Authors: G. Wiselin Jiji
Addresses: Department of Computer Science & Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur 628215, Tamil Nadu, India
Abstract: Detecting brain structural changes from magnetic resonance (MR) images can facilitate early diagnosis and treatment of Multiple Sclerosis (MS), a neurodegenerative disease of central nervous system. We develop a novel volume and shape of hippocampus-based feature with Support Vector Machine (SVM) to detect brain structural changes as potential biomarkers. This approach requires pre-processing which is influenced by artefacts such as image distortion. We represent hippocampus segmentation based on watershed bottom hat filtering algorithm and morphological operations. The extracted features are used as criteria to categorise image features into two classes, i.e. healthy and patient. Only healthy and patient features are used to predict the disease status of new brain images. The results proved that the proposed architecture has high contribute to computer-aided diagnosis of MS. Our empirical evaluation has a superior retrieval and diagnosis performance when compared to the performance of other works.
Keywords: multiple sclerosis; cognition; hippocampus; depression; image processing; brain changes; structural changes; magnetic resonance imaging; MRI images; early diagnosis; MS treatment; support vector machines; SVM; biomarkers; image distortion; image segmentation; watershed bottom hat filtering; morphological operations; feature extraction; image features; brain images.
International Journal of Biomedical Engineering and Technology, 2016 Vol.20 No.4, pp.369 - 387
Received: 17 Jun 2015
Accepted: 23 Sep 2015
Published online: 17 May 2016 *