A Comparative Analysis of Medical Image Fusion Techniques: A Variety of Approaches

The goal of medical image fusion is to combine complementary data from several imaging modalities to improve research, diagnosis, and therapy and research by integrating complementary data gathered from several imaging modalities. In this research, Four distinct methodologies are used in this study to investigate medical image fusion: Laplacian re-decomposition (LRD) fusion methodology, Discrete Wavelet Transform (DWT), Simple Average, and Multi-Level Morphological Gradient Pulse Coupled Neural Network (MLMG PCNN).