Nuclear Magnetic Image Segmentation of Rectal Cancer Based on Improved Genetic Neural Network

Abstract

Image segmentation is the basis of image analysis and understanding, and has an unshakable position in the field of computer vision. In order to improve the accuracy of nuclear magnetic image segmentation of rectal cancer, this paper proposes an improved genetic neural network algorithm for the problems of traditional BP neural network algorithm. In order to enhance the network performance, this paper improves the genetic neural network from the two aspects of fitness function and genetic operator, which makes the training speed and convergence precision greatly improved. Target samples were analyzed by image histogram analysis, and the improved genetic neural network was used to learn the samples to obtain the training network. Taking the pixel matrix of the image as the input vector, it is put into the trained network for classification, and finally the segmentation is realized. The simulation experiment proves that compared with the classical image segmentation method, the improved genetic neural network image segmentation method has a good segmentation effect and is a feasible image segmentation method.