English

Deep learning classification of chest x-ray images

Image and Video Processing 2020-06-24 v2 Machine Learning

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

Cite

@article{arxiv.2005.09609,
  title  = {Deep learning classification of chest x-ray images},
  author = {Mohammad S. Majdi and Khalil N. Salman and Michael F. Morris and Nirav C. Merchant and Jeffrey J. Rodriguez},
  journal= {arXiv preprint arXiv:2005.09609},
  year   = {2020}
}

Comments

4 pages, 4 figures, 2 tables, conference , SSIAI 2020

R2 v1 2026-06-23T15:40:02.653Z