@inproceedings{46d44b40c0ce47dd9b32fe6dd5786b43,
title = "Deep Learning Classification of Chest X-Ray Images",
abstract = "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.",
keywords = "cardiomegaly, chest X-ray, classification, deep learning, pulmonary nodule",
author = "Majdi, {Mohammad S.} and Salman, {Khalil N.} and Morris, {Michael F.} and Merchant, {Nirav C.} and Rodriguez, {Jeffrey J.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 ; Conference date: 29-03-2020 Through 31-03-2020",
year = "2020",
month = mar,
doi = "10.1109/SSIAI49293.2020.9094612",
language = "English (US)",
series = "Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "116--119",
booktitle = "2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings",
}