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width=\"1053\" alt=\"radtorch_1 0_header\" src=\"https://user-images.githubusercontent.com/17037319/163655603-d863a52f-3622-4e7f-925d-9635a675180e.png\"\u003e\n\n![](https://img.shields.io/badge/stable%20version-01.0.1-brightgreen)\n![](https://img.shields.io/badge/preview%20version-01.0.1-red)\n![](https://img.shields.io/badge/dependencies-up%20to%20date-blue)\n![](https://img.shields.io/badge/license-AGPL3.0-inactive)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6464087.svg)](https://doi.org/10.5281/zenodo.6464087)\n\n\n\n## What is RADTorch ?\n\u003cp style='text-align: justify;'\u003e\n\nRADTorch provides a framework of higher level classes and functions that significantly reduce the time needed for implementation of different machine and deep learning algorithms on DICOM and non-DICOM medical images.\n\nRADTorch was built by radiologists for radiologists so they can build, test and implement state-of-the-art machine learning algorithms in minutes.\n\nRADTorch is :\n\n- User-Friendly: Minimal coding required.\n\n- Comprehensive: Includes data analysis and visualization.\n\n- Backed by state-of-the-art machine learning and data visualization frameworks.\n\n\u003c/p\u003e\n\n\n![image](https://user-images.githubusercontent.com/17037319/163655659-bc7744f1-db9a-425a-95c8-202a6322536f.png)\n\n\n## Install RADTorch\n### Stable version\nTo install stable version via pip, use the following command:\n\n```\npip3 install git+https://download.radtorch.com/\n```\n\nPreview version\nTo install Preview beta version via pip, use the following command:\n```\npip3 install git+https://preview.radtorch.com/\n```\n\n\u003cbr\u003e\n\n### Requests\nFeature requests are more than welcomed on our discussion board [HERE](https://github.com/radtorch/radtorch/issues/4#issue-573590182)\n\n\u003cbr\u003e\n\n\n### Contribute\nBug reports and pull requests are welcome.\n\n\u003cbr\u003e\n\n### Cite us\n\n```\n@software{mohamed_elbanan_2022_6464087,\n  author       = {Mohamed Elbanan},\n  title        = {radtorch/radtorch: 1.0.0},\n  month        = apr,\n  year         = 2022,\n  publisher    = {Zenodo},\n  version      = {1.0.0},\n  doi          = {10.5281/zenodo.6464087},\n  url          = {https://doi.org/10.5281/zenodo.6464087}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fradtorch%2Fradtorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fradtorch%2Fradtorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fradtorch%2Fradtorch/lists"}