Graph Theory for Computer Science

13Graph Unveiling in Image Processing: A Comprehensive Study of Recognition and Segmentation Methods in Medical Images

M. Indira, M. Midhula* and S. Vishnupriya

Department of Computer Science, P.K.R. Arts College for Women (Autonomous), Gobichettipalayam, India

Abstract

Accurate diagnosis and treatment planning are made possible by medical image processing, which is essential to contemporary healthcare. The novel use of graph-based algorithms for medical image processing is explored in this study, with a particular emphasis on segmentation and recognition methods. The article offers a thorough overview of the opportunities and difficulties at the nexus of graphs and medical image processing by thoroughly reviewing the body of prior research, current techniques, and cutting-edge developments.

The research’s segmentation component highlights how important it is to accurately identify anatomical features and lesions in medical images. A variety of graph-based methods are investigated in relation to clinical image segmentation, including graph cuts, random walks, and graph convolutional networks. The topic includes how well these methods handle a variety of medical data types and how flexible they are to various imaging modalities. The focus of recognition techniques is on the meaningful feature extraction from medical images. Graph-based techniques for feature representation and classification are examined, demonstrating how they can improve the precision of diagnoses and support ...