Artificial Intelligence-based Medical Image Fusion Analysis for Early Detection of Alzheimer’s disease

Abstract

This research work investigated a selection of fundamental research projects that helped develop the development
of medical image fusion in the initial course of study that we intended for the adaptive pulse-coupled neural
network. As time progresses, Alzheimer’s disease (AD) detection affected individuals can feel the severity of the
condition by finding it increasingly difficult to recall recent events, and they also find it hard to engage in logical
reasoning or recognize familiar faces. The introduction and innovation in the field of advanced neuroimaging
technologies have contributed to an excellent level of support for such tools in AD diagnosis. By deploying these
approaches, investigators are able to understand better the complicated structural and functional relationships
within the nervous system and identify the clinical alterations that mark AD. The results of these investigations
not only provide an anchor for the proposed technique, but they show information on the evolution of methods
regarding this area of study