SURVEY ON MEDICAL IMAGE SEGMENTATION BASED ON MULTI-MODAL CONVOLUTIONAL NEURAL NETWORK

Abstract

Image fusion is a procedure of mixing the correlative just as the basic highlights of a lot of images, to produce a resultant image with predominant data content as far as abstract just as target examination perspective. A definitive point of medical image fusion can be comprehensively characterized as the mix of visual data contained in any number of info medical images into a single combined image without presenting twisting or data misfortune. The neural network way to deal with produce effective characterization rules. Convolution neural network calculation is a multilayer perceptron that is the uncommon plan for ID of two-dimensional information data. Continuously have more layers: input layer, convolution layer, test layer and yield layer. Profound learning alludes to the sparkling part of AI that depends on learning dimensions of portrayals. Convolutional Neural Networks (CNN) is one sort of profound neural network. This paper talked about Medical image segmentation procedures, techniques and their convolutional neural network.