Edge Detection Algorithm of MRI Medical Image Based on Artificial Neural Network

• Published in: Procedia computer science Vol. 208; pp. 136 - 144
• Main Authors: Yunhong, Shao, Shilei, Yuan, Xiaojing, Zhou, Jinhua, Ye
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2022
• Subjects: artificial neural network; canny operator; edge detection; MRI medical image; MRI medical image; artificial neural network; edge detection; canny operator
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2022.10.021

In order to be able to extract useful information from MRI medical images, we need to carry out effective image segmentation of MRI medical image and use appropriate operators to detect the edge of the image. Firstly, this paper adopts a research method based on the characteristics of horizontal, vertical and diagonal differences, and then carries out comparative analysis on different operators from different perspectives such as frequency domain and velocity domain. After analyzing the results, it is concluded that: Canny operator can detect complete, continuous and detailed edges at a faster speed. This paper uses edge detector based on Canny operator as the training output of artificial neural network. By training artificial neural network. The optimized parameters were obtained, and subjective analysis and computational analysis were performed on the quality of edge detection results of MRI medical images based on different methods. The results show that compared with the single Sobel, Canny and other traditional operators, the edge information of MRI medical image obtained by the neural network-based edge detection method is more complete and its processing time is nearly 3 times faster than the traditional edge detection method.