A Convolutional Neural Network Approach for Classifying Leukocoria

被引：0

作者：

Henning, Ryan ^{[1
]}

Rivas-Perea, Pablo ^{[1
]}

Shaw, Bryan ^{[2
]}

Hamerly, Greg ^{[1
]}

机构：

[1] Baylor Univ, Dept Comp Sci, Waco, TX 76798 USA

[2] Baylor Univ, Dept Chem, Waco, TX 76798 USA

来源：

2014 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION (SSIAI 2014) | 2014年

关键词：

machine learning; retinoblastoma; leukocoria;

D O I：

暂无

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 Convolutional Neural Networks to detect leukocoria, or white-eye reflections, in recreational photography. Leukocoria is the most prominent symptom of retinoblastoma, a solid-tumor cancer of the eye that occurs most often in young children. We trained several networks for the task, using training images downloaded from Flickr. We achieved low error rates (< 3%) for classification of eye images into three classes: normal, leukocoric, and pseudo-leukocoric. We also provide a method for tuning the outputs of a trained network to match desired true-positive/false-positive rates.

引用

页码：9 / 12

页数：4

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