MRI Image Segmentation Using Bat Optimization Algorithm with Fuzzy C Means (BOA-FCM) Clustering
Functional and anatomical information extraction from Magnetic Resonance Images (MRI) is important in medical image applications. The information extraction is highly influenced by the artifacts in the MRI images. The feature extraction involves the segmentation of MRI images. We present
a MRI image segmentation using Bat Optimization Algorithm (BOA) with Fuzzy C Means (FCM) clustering. Echolocation of bats is utilized in Bat Optimization Algorithm. The proposed segmentation technique is evaluated with existing segmentation techniques. Results of experimentation shows that
proposed segmentation technique outperforms existing methods and produces 98.5% better results.
Keywords: Bat Optimization Algorithm; Fuzzy C Means; Magnetic Resonance Images
Document Type: Research Article
Affiliations: 1: Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore 641407, India 2: Anurag Univeristy, Hyderabad 500038, India 3: Electronics and Communication Engineering, Government Engineering College, Palakkad 678008, India
Publication date: 01 March 2021
- Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites
Receive new issue alert- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content