Enhancing Medical Image Fusion with Deep Learning-Based Texture-Aware Feature Mapping (KEY IJP************863)

• Doppani Balaji,N.vishnu Vardhan Reddy,B.phani Chandra,P.ramthertham Reddy

Abstract

Medical image analysis is essential to healthcare because it helps radiologists and doctors make accurate diagnoses by providing them with specific insights from various imaging modalities. However, due to the complex nature of medical data, it is sometimes necessary to integrate data from multiple modalities in order to provide a comprehensive understanding of the ROI. In order to support clinical diagnosis, this work attempts to merge pathology data from two distinct multimodal pictures of the same region of interest. To direct the fusing of data from input picture matrices, robust fusion weights are generated in the form of individually weighted matrices. Key information is extracted using the quick gray-level co-occurrence matrix-mean approach. characteristics of texture required for the fusion process. The quality of the fusion is assessed by a comprehensive validation process that employs standard criteria and objective analysis. The efficacy and superiority of the suggested strategy will be evaluated by contrasting it with current fusion techniques.