Design of a Robust Hybrid Fuzzy Method for Medical Image Fusion

Abstract

In this modern era, medical image  processing is an indispensable part of many applications and  practices in the medical domain. The images that are used  should meet certain criteria, including having more accurate  details and information than each individual image, which  can help medical scientists with analysis and treatment.  Medical image fusion is among the techniques that offer  high-quality images, which are combined from different  modalities. Multimodal medical image fusion provides  remarkable improvement in the quality of the fused images.  In this paper, we describe an image fusion method for  magnetic resonance imaging (MRI) and computed  tomography (CT) utilizing local features and fuzzy logic  methods. The aim of the proposed technique is to create the  maximum combination of useful information present in MRI  and CT images. Image local features are distinguished and  combined with fuzzy logic to calculate weights for each pixel. Simulation outcomes show that the proposed method  produces considerably better results compared to cutting edge techniques. The method is also used to detect and  highlight tumorous areas, followed by morphology filters  used to eliminate any noise and disturbance.