Machine learning approaches in medical image analysis: From detection to diagnosis

被引：212
作者：
de Bruijne, Marleen [1 ,2 ,3 ,4 ]
机构：
[1] Erasmus MC Univ Med Ctr Rotterdam, Dept Med Informat, Biomed Imaging Grp Rotterdam, Rotterdam, Netherlands
[2] Erasmus MC Univ Med Ctr Rotterdam, Dept Radiol, Biomed Imaging Grp Rotterdam, Rotterdam, Netherlands
[3] Erasmus MC Univ Med Ctr Rotterdam, Dept Nucl Med, Biomed Imaging Grp Rotterdam, Rotterdam, Netherlands
[4] Univ Copenhagen, Dept Comp Sci, Image Sect, DK-1168 Copenhagen, Denmark
来源：
MEDICAL IMAGE ANALYSIS | 2016年 / 33卷
关键词：
Machine learning; Classification; Computer aided diagnosis; Transfer learning; SEGMENTATION;
D O I：
10.1016/j.media.2016.06.032
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols, learning from weak labels, and interpretation and evaluation of results. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：94 / 97
页数：4
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