Title: A novel approach for assessing the damaged region in MRI through improvised GA and SGO

Authors: P. Naga Srinivasu; G. Srinivas; T. Srinivasa Rao; Valentina E. Balas

Addresses: Department of CSE, GIT, Gitam University, Visakhapatnam, AP, India ' Department of IT, Anil Neerukonda Institute of Technology and Sciences, Sangivalasa, AP, India ' Department of CSE, GIT, Gitam University, Visakhapatnam, AP, India ' Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, 77 B-dul Revolutiei, 310130 Arad, Romania

Abstract: A plethora of magnetic resonance (MR) image segmentation methods exist in the published literature but most of them fail at recognising small regions in MR images accurately due to inefficient segmentation techniques. Through this article, we propose a novel and efficient MRI image segmentation technique which employs an improvised genetic algorithm (GA) based on twin point cross over mutation for automated segmentation. The resultant image from GA is used as an input for social group optimisation technique (SGO), and a lightweight computationally efficient algorithm for refining the segmented image. We have carried out an experiment on benchmark and real time images to compare the proposed technique with the existing segmentation methods which use teacher learner-based optimisation (TLBO). We have observed that proposed approach exhibits better performance over its counterpart.

Keywords: harmonic mean; genetic algorithm; social group optimisation; SGO; Laplacian; magnetic resonance imaging; MRI.

DOI: 10.1504/IJAIP.2024.143818

International Journal of Advanced Intelligence Paradigms, 2024 Vol.29 No.4, pp.348 - 363

Received: 02 May 2018
Accepted: 11 Jan 2019
Published online: 08 Jan 2025 *

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