Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis

被引:8
作者
Bosnacki, Dragan [1 ]
van Riel, Natal [1 ]
Veta, Mitko [1 ]
机构
[1] Eindhoven Univ Technol, Dept Biomed Engn, Eindhoven, Netherlands
来源
AUTOMATED REASONING FOR SYSTEMS BIOLOGY AND MEDICINE | 2019年 / 30卷
关键词
NEOCOGNITRON;
D O I
10.1007/978-3-030-17297-8_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the recent years, deep learning based methods and, in particular, convolutional neural networks, have been dominating the arena of medical image analysis. This has been made possible both with the advent of new parallel hardware and the development of efficient algorithms. It is expected that future advances in both of these directions will increase this domination. The application of deep learning methods to medical image analysis has been shown to significantly improve the accuracy and efficiency of the diagnoses. In this chapter, we focus on applications of deep learning in microscopy image analysis and digital pathology, in particular. We provide an overview of the state-of-the-art methods in this area and exemplify some of the main techniques. Finally, we discuss some open challenges and avenues for future work.
引用
收藏
页码:453 / 469
页数:17
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