MRI Image Segmentation Using Bat Optimization Algorithm with Fuzzy C Means (BOA-FCM) Clustering

B. Jai Shankar, K. Murugan, A. Obulesu, S. Finney Daniel Shadrach, R. Anitha

2020Journal of Medical Imaging and Health Informatics35 citationsDOI

Abstract

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.

Topics & Concepts

Artificial intelligenceSegmentationCluster analysisPattern recognition (psychology)Computer scienceImage segmentationHuman echolocationFuzzy logicSegmentation-based object categorizationComputer visionScale-space segmentationFeature extractionFuzzy clusteringBiologyNeuroscienceMedical Image Segmentation TechniquesBrain Tumor Detection and ClassificationDigital Imaging for Blood Diseases