Design and implementation of a MATLAB GUI-based multimodal medical image fusion system

Abstract

In clinical practice, the use of multimodal medical images is becoming more important in diagnosis, disease monitoring, and treatment planning. In clinical practice, because medical image information is limited to tissue or pathological information, this study designed a multimodal medical image fusion simulation system. This system achieves early disease diagnosis by precisely aligning and integrating multiple medical image modalities, enabling multimodal intelligent diagnosis. It uses multimodal methods for image registration and fusion and validates the fusion methodology with objective evaluation metrics to ensure the system's stability and accuracy across various datasets. The experimental results show that the average gradient value, the information entropy value, and the standard deviation value of the fused image are much better than those of the two source images. These improvements increase the information content of the image and improve its spatial resolution. The system is validated using several sets of clinical medical images, investigates its application in the medical field, and provides auxiliary medical diagnostic assistance to clinical practice.