Benign and Malignant Tumor Identification by Fusion Technique using SVM Model

Medical image fusion plays a vital role in the medical field to diagnose brain tumors which be classified as benign or malignant. It is a procedure of amalgamate multiple image of the same scene into a single fused image to reduce unreliability and minimizing errors while extracting all the useful information from the source image. SVM is used to fuse two brain images with different visions. Concluding fused image will be more informative than the source images. The texture and wavelet feature are extracted from the fused image. SVM classifier classifies brain tumors based on trained and tested features. Apparently proposed method achieved 80.48% sensitivity, 99.9% specificity and 99.96% accuracy. Experimental results obtained from the fusion process demonstrate that the use of proposed image fusion approach shows better performance while compared with conventional fusion methodologies.