TorchXRayVision: A library of chest X-ray datasets and models

Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand
Proceedings of The 5th International Conference on Medical Imaging with Deep Learning, PMLR 172:231-249, 2022.

Abstract

TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models. It provides a common interface and common pre-processing chain for a wide set of publicly available chest X-ray datasets. In addition, a number of classification and representation learning models with different architectures, trained on different data combinations, are available through the library to serve as baselines or feature extractors.

Cite this Paper

BibTeX
@InProceedings{pmlr-v172-cohen22a, title = {TorchXRayVision: A library of chest X-ray datasets and models}, author = {Cohen, Joseph Paul and Viviano, Joseph D. and Bertin, Paul and Morrison, Paul and Torabian, Parsa and Guarrera, Matteo and Lungren, Matthew P and Chaudhari, Akshay and Brooks, Rupert and Hashir, Mohammad and Bertrand, Hadrien}, booktitle = {Proceedings of The 5th International Conference on Medical Imaging with Deep Learning}, pages = {231--249}, year = {2022}, editor = {Konukoglu, Ender and Menze, Bjoern and Venkataraman, Archana and Baumgartner, Christian and Dou, Qi and Albarqouni, Shadi}, volume = {172}, series = {Proceedings of Machine Learning Research}, month = {06--08 Jul}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v172/cohen22a/cohen22a.pdf}, url = {https://proceedings.mlr.press/v172/cohen22a.html}, abstract = {TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models. It provides a common interface and common pre-processing chain for a wide set of publicly available chest X-ray datasets. In addition, a number of classification and representation learning models with different architectures, trained on different data combinations, are available through the library to serve as baselines or feature extractors.} }
Endnote
%0 Conference Paper %T TorchXRayVision: A library of chest X-ray datasets and models %A Joseph Paul Cohen %A Joseph D. Viviano %A Paul Bertin %A Paul Morrison %A Parsa Torabian %A Matteo Guarrera %A Matthew P Lungren %A Akshay Chaudhari %A Rupert Brooks %A Mohammad Hashir %A Hadrien Bertrand %B Proceedings of The 5th International Conference on Medical Imaging with Deep Learning %C Proceedings of Machine Learning Research %D 2022 %E Ender Konukoglu %E Bjoern Menze %E Archana Venkataraman %E Christian Baumgartner %E Qi Dou %E Shadi Albarqouni %F pmlr-v172-cohen22a %I PMLR %P 231--249 %U https://proceedings.mlr.press/v172/cohen22a.html %V 172 %X TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models. It provides a common interface and common pre-processing chain for a wide set of publicly available chest X-ray datasets. In addition, a number of classification and representation learning models with different architectures, trained on different data combinations, are available through the library to serve as baselines or feature extractors.
APA
Cohen, J.P., Viviano, J.D., Bertin, P., Morrison, P., Torabian, P., Guarrera, M., Lungren, M.P., Chaudhari, A., Brooks, R., Hashir, M. & Bertrand, H.. (2022). TorchXRayVision: A library of chest X-ray datasets and models. Proceedings of The 5th International Conference on Medical Imaging with Deep Learning, in Proceedings of Machine Learning Research 172:231-249 Available from https://proceedings.mlr.press/v172/cohen22a.html.

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