A Novel Multimodal Anatomical Medical Image Fusion Using Structure Extraction

Abstract

The significant advancement in medical imaging methodology is a multimodal medical image fusion method. Its primary goal is to provide a complete overview of medical image fusion methods, including theoretical foundations and recent breakthroughs. The primary goal is to gather useful information by merging several images obtained from different sources into a single image appropriate for better diagnosis. Magnetic Resonance Imaging (MRI) aids professionals’ decision making during the aided diagnostic pipeline in medical techniques such as Computed Tomography (CT). The fused image, on the other hand, may aid in the performance of other tasks such as classification, detection, and segmentation. The suggested technique eliminates distortion from the source image in the first step, followed by image enhancement, weight extraction, weight map computation and refining, pyramid decomposition, and output fused image. Matlab programming tool is utilized for this procedure, and the authors can customize the parameter settings. In this experiment, we focus on qualitative rather than quantitative analyses. The method’s conclusion is that current multimodal medical image fusion study findings are more relevant and might be used to successfully diagnose patients.