DEEP LEARNING CLASSIFICATION OF CHEST X-RAY IMAGES

被引:0
|
作者
Majdi, Mohammad S. [1 ,3 ]
Salman, Khalil N. [2 ]
Morris, Michael F. [4 ]
Merchant, Nirav C. [3 ]
Rodriguez, Jeffrey J. [1 ]
机构
[1] Univ Arizona, Dept Elect & Comp Engn, Tucson, AZ 85721 USA
[2] Univ Arizona, Dept Med Imaging, Tucson, AZ USA
[3] Univ Arizona, Data Sci Inst, Tucson, AZ 85724 USA
[4] Univ Arizona, Dept Radiol, Phoenix, AZ USA
关键词
chest X-ray; deep learning; classification; pulmonary nodule; cardiomegaly; TUBERCULOSIS;
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 propose a deep learning based method for classification of commonly occurring pathologies in chest X-ray images. The vast number of publicly available chest X-ray images provides the data necessary for successfully employing deep learning methodologies to reduce the misdiagnosis of thoracic diseases. We applied our method to the classification of two example pathologies, pulmonary nodules and cardiomegaly, and we compared the performance of our method to three existing methods. The results show an improvement in AUC for detection of nodules and cardiomegaly compared to the existing methods.
引用
收藏
页码:116 / 119
页数:4
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