Deep learning classification of chest x-ray images

• URL: http://arxiv.org/abs/2005.09609v2
• Date: Mon, 22 Jun 2020 19:42:03 GMT
• Title: Deep learning classification of chest x-ray images
• Authors: Mohammad S. Majdi, Khalil N. Salman, Michael F. Morris, Nirav C. Merchant, Jeffrey J. Rodriguez
• Abstract summary: We propose a deep learning based method for classification of commonly occurring pathologies in chest X-ray images. We applied our method to the classification of two example pathologies, pulmonary nodules and cardiomegaly. The results show an improvement in AUC for detection of nodules and cardiomegaly compared to the existing methods.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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