Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks

被引：1018

作者：

Ciresan, Dan C. ^{[1
]}

Giusti, Alessandro ^{[1
]}

Gambardella, Luca M. ^{[1
]}

Schmidhuber, Juergen ^{[1
]}

机构：

[1] IDSIA, Dalle Molle Inst Artificial Intelligence, USI SUPSI, Lugano, Switzerland

来源：

MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2013, PT II | 2013年 / 8150卷

关键词：

RECOGNITION;

D O I：

10.1007/978-3-642-40763-5_51

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We use deep max-pooling convolutional neural networks to detect mitosis in breast histology images. The networks are trained to classify each pixel in the images, using as context a patch centered on the pixel. Simple postprocessing is then applied to the network output. Our approach won the ICPR 2012 mitosis detection competition, outperforming other contestants by a significant margin.

引用

页码：411 / 418

页数：8

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