Multi-Modality Medical Image Fusion for Reliable and Accurate Diagnosis

Multi-Modality Medical Image Fusion for Reliable and Accurate Diagnosis

Dhanushree A N 1,Prafulla K S2, S Anusha3, Simran Taj A4, Sumaiya Seher R5
1 Faculty in Department of Computer Science Engineering, S J C Institute of Technology, Chikkaballapur, India

2,3,4,5 Department of Computer Science Engineering, S J C Institute of Technology, Chikkaballapur, India

Abstract: The image fusion process is characterized as collecting all of the important information from multiple images, as well as its inclusion in fewer, usually one, images. There is indeed the solution to Problems with the various images, such as multi-focus images and medical images through a simulation process using images to the fuse's work based on previously abused fusion techniques such as convolutional neural networks. To obtain a fused image with high visual quality and clear structure details, convolutional neural network (CNN) based medical image fusion algorithm is proposed. The proposed algorithm uses the trained Siamese convolutional network to fuse the pixel activity information of source images to realize the generation of the weight map. The results of the experiment carried out to show that“Multi-Modality Medical Image Fusion” for reliable and accurate diagnosis of 90% of fused images.

KeyWords: MRI Image, CT Image, Image fusion, Convolutional neural network, Wavelet Transform.