Application of semantic segmentation based on convolutional neural network in medical images.
10.7507/1001-5515.201906067
- Author:
Yuchao WU
1
;
Lan LIN
1
;
Jingxuan WANG
1
;
Shuicai WU
1
Author Information
1. College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100124, P.R.China.
- Publication Type:Journal Article
- Keywords:
convolutional neural network;
medical application;
semantic segmentation
- From:
Journal of Biomedical Engineering
2020;37(3):533-540
- CountryChina
- Language:Chinese
-
Abstract:
With the rapid development of network structure, convolutional neural networks (CNN) consolidated its position as a leading machine learning tool in the field of image analysis. Therefore, semantic segmentation based on CNN has also become a key high-level task in medical image understanding. This paper reviews the research progress on CNN-based semantic segmentation in the field of medical image. A variety of classical semantic segmentation methods are reviewed, whose contributions and significance are highlighted. On this basis, their applications in the segmentation of some major physiological and pathological anatomical structures are further summarized and discussed. Finally, the open challenges and potential development direction of semantic segmentation based on CNN in the area of medical image are discussed.
