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

Keywords: Chest X-ray, CXR, pre-trained models, datasets, representation learning, generalization, feature extraction, PyTorch

TL;DR: A library for chest X-ray datasets and models. Including pre-trained models.

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.

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Paper Type: validation/application paper

Primary Subject Area: Application: Radiology

Secondary Subject Area: Unsupervised Learning and Representation Learning

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Code And Data: https://github.com/mlmed/torchxrayvision

Community Implementations: [ 2 code implementations](https://www.catalyzex.com/paper/arxiv:2111.00595/code)