Exploring and analyzing the improvement mechanism of U-Net and its application in medical image segmentation.
10.7507/1001-5515.202111010
- Author:
Tao ZHOU
1
;
Senbao HOU
1
;
Huiling LU
2
;
Yanan ZHAO
1
;
Pei DANG
1
;
Yali DONG
1
Author Information
1. School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, P. R. China.
2. School of Science, Ningxia Medical University, Yinchuan 750004, P. R. China.
- Publication Type:Journal Article
- Keywords:
Improvement mechanism;
Medical image;
Network structure;
Semantic segmentation;
U-Net
- MeSH:
Image Processing, Computer-Assisted/methods*
- From:
Journal of Biomedical Engineering
2022;39(4):806-825
- CountryChina
- Language:Chinese
-
Abstract:
Remarkable results have been realized by the U-Net network in the task of medical image segmentation. In recent years, many scholars have been researching the network and expanding its structure, such as improvement of encoder and decoder and improvement of skip connection. Based on the optimization of U-Net structure and its medical image segmentation techniques, this paper elucidates in the following: First, the paper elaborates on the application of U-Net in the field of medical image segmentation; Then, the paper summarizes the seven improvement mechanism of U-Net: dense connection mechanism, residual connection mechanism, multi-scale mechanism, ensemble mechanism, dilated mechanism, attention mechanism, and transformer mechanism; Finally, the paper states the ideas and methods on the U-Net structure improvement in a bid to provide a reference for later researches, which plays a significant part in advancing U-Net.
