Author(s)

Shaohua Wang¹, Jianli Jiang², Xiaobing Lu³

¹The Second People’s Hospital of Yichang, Yichang, China.
²The First People’s Hospital of Yichang, Yichang, China.
³The Institute of Mechanics, Chinese Academy of Sciences, Beijing, China.

Image technology is applied more and more to help doctors to improve the accuracy of tumor diagnosis as well as researchers to study tumor characteristics. Image segmentation technology is an important part of image treatment. This paper summarizes the advances of image segmentation by using artificial neural network including mainly the BP network and convolutional neural network (CNN). Many CNN models with different structures have been built and successfully used in segmentation of tumor images such as supervised and unsupervised learning CNN. It is shown that the application of artificial network can improve the efficiency and accuracy of segmentation of tumor image. However, some deficiencies of image segmentation by using artificial neural network still exist. For example, new methods should be found to reduce the cost of building the marked data set. New artificial networks with higher efficiency should be built.

Artificial Neural Network, Segmentation of Tumor Image, Convolutional Neural Network

Wang, S. , Jiang, J. and Lu, X. (2020) Advances on Tumor Image Segmentation Based on Artificial Neural Network. Journal of Biosciences and Medicines, 8, 55-62. doi: 10.4236/jbm.2020.87006.