深度学习
计算机科学
人工智能
计算机辅助设计
医学影像学
领域(数学)
癌症
分割
机器学习
医学物理学
数据科学
医学
工程类
工程制图
内科学
数学
纯数学
作者
Shihui Chen,Weixiang Liu,Jing Qin,Liangliang Chen,Guo Bin,Yuxiang Zhou,Tianfu Wang,Bingsheng Huang
出处
期刊:PubMed
[National Institutes of Health]
日期:2017-04-25
卷期号:34 (2): 314-319
被引量:15
标识
DOI:10.7507/1001-5515.201609047
摘要
The dramatically increasing high-resolution medical images provide a great deal of useful information for cancer diagnosis, and play an essential role in assisting radiologists by offering more objective decisions. In order to utilize the information accurately and efficiently, researchers are focusing on computer-aided diagnosis (CAD) in cancer imaging. In recent years, deep learning as a state-of-the-art machine learning technique has contributed to a great progress in this field. This review covers the reports about deep learning based CAD systems in cancer imaging. We found that deep learning has outperformed conventional machine learning techniques in both tumor segmentation and classification, and that the technique may bring about a breakthrough in CAD of cancer with great prospect in the future clinical practice.
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