Medical Image Fusion for Brain Tumor Detection (International Journal of Food and Nutritional Sciences, 2022)
Medical image fusion is an important task in medical diagnosis that aims to provide acomplete representation of medical images by combining multiple imaging modalities. Thefused image is then fed into deep learning algorithms for tumor classification. In this paper,we propose an approach for medical image fusion of CT and MRI scan images for braintumor detection. This work proposes an algorithm for the fusion of several imagingmodalities, such as MRI and CT, based on a classifier with a fusion rule. Several qualitativeand quantitative evaluation metrics have been used to assess the performance of theproposed method and compare it to cutting-edge image fusion techniques. On the basis ofmetrics like standard deviation, entropy, mutual information, etc., the experimentalfindings are assessed. In terms of accuracy and training loss metrics, the experimentalresults show that the proposed approach outperforms the individual modalities. As a result,the suggested technique can be employed as an effective and accurate instrument for thedetection of brain cancers. The method can be used to increase diagnosis precision anddecrease the false-negative rate, which will ultimately improve patient outcomes