Deep Learning Applications in Medical Image Analysis

被引:770
作者
Ker, Justin [1 ]
Wang, Lipo [2 ]
Rao, Jai [1 ]
Lim, Tchoyoson [3 ]
机构
[1] Natl Neurosci Inst, Dept Neurosurg, Singapore 308433, Singapore
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[3] Natl Neurosci Inst, Dept Neuroradiol, Singapore 308433, Singapore
来源
IEEE ACCESS | 2018年 / 6卷
关键词
Convolutional neural networks; medical image analysis; machine learning; deep learning; CONVOLUTIONAL NEURAL-NETWORKS; BRAIN-TUMOR SEGMENTATION; CLASSIFICATION; CANCER; AUTOENCODERS; INTEGRATION; ALGORITHM; DATASET; NODULES; NUCLEI;
D O I
10.1109/ACCESS.2017.2788044
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The tremendous success of machine learning algorithms at image recognition tasks in recent years intersects with a time of dramatically increased use of electronic medical records and diagnostic imaging. This review introduces the machine learning algorithms as applied to medical image analysis, focusing on convolutional neural networks, and emphasizing clinical aspects of the field. The advantage of machine learning in an era of medical big data is that significant hierarchal relationships within the data can be discovered algorithmically without laborious hand-crafting of features. We cover key research areas and applications of medical image classification, localization, detection, segmentation, and registration. We conclude by discussing research obstacles, emerging trends, and possible future directions.
引用
收藏
页码:9375 / 9389
页数:15
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