Published Paper Details:

In the medical field, medical image fusion plays an important role in diagnosis of brain tumors that may be classified as malignant or benign. To cut back uncertainty and minimize redundancy whereas extracting all the helpful info from the supply pictures, it's the method of grouping multiple pictures of the identical scene into one united image. SVM is employed to fuse 2 totally different visions brain tomography pictures. The image united is going to be a lot more informative than the pictures from the supply. The image united allows us to extract the characteristics of texture and wavelet. Based on supported trained and tested options, the SVM Classifier classifies brain tumors. The planned technique achieved sensitivity of 80.48 percent, accuracy of 99.69 percent and specificity of 99.9 percent. Experimental results obtained from the fusion method show that the utilization of the planned approach to image fusion shows higher performance compared to standard fusion methodologies.