TorchXRayVision
An open-source library providing chest X-ray datasets, pre-trained models, and tools for medical imaging research and analysis.
What is TorchXRayVision?
TorchXRayVision is an open-source software library for chest X-ray analysis, providing a common interface for multiple public datasets and a collection of pre-trained deep learning models. It solves the problem of inconsistent data formats and redundant model training in medical imaging research by offering standardized preprocessing and reusable feature extractors. The library includes classifiers, autoencoders, and segmentation models trained on large cohorts like NIH, CheXpert, and MIMIC-CXR.
Medical imaging researchers and data scientists working on chest X-ray analysis, particularly those developing algorithms for pathology detection or studying model generalization across datasets. It's also valuable for clinicians seeking to apply pre-trained models for rapid dataset analysis.
Developers choose TorchXRayVision for its comprehensive collection of standardized datasets and pre-trained models, which significantly reduce setup time and enable robust cross-dataset evaluation. Its unique value lies in providing tools for studying distribution shifts and feature reuse, which are critical for reliable medical AI research.
Overview
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
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