Metadata-Version: 2.1
Name: dosma
Version: 0.0.13rc1
Summary: An AI-powered open-source medical image analysis toolbox
Home-page: https://github.com/ad12/DOSMA
Author: Arjun Desai
License: GNU
Project-URL: Documentation, https://dosma.readthedocs.io/
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
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# DOSMA: Deep Open-Source Medical Image Analysis
[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
![GitHub Workflow Status](https://img.shields.io/github/workflow/status/ad12/DOSMA/CI)
[![codecov](https://codecov.io/gh/ad12/DOSMA/branch/master/graph/badge.svg?token=X2FRQJHV2M)](https://codecov.io/gh/ad12/DOSMA)
[![Documentation Status](https://readthedocs.org/projects/dosma/badge/?version=latest)](https://dosma.readthedocs.io/en/latest/?badge=latest)

[Documentation](http://dosma.readthedocs.io/) | [Questionnaire](https://forms.gle/sprthTC2swyt8dDb6) | [DOSMA Basics Tutorial](https://colab.research.google.com/drive/1zY5-3ZyTBrn7hoGE5lH0IoQqBzumzP1i?usp=sharing)

DOSMA is an AI-powered Python library for medical image analysis. This includes, but is not limited to:
- image processing (denoising, super-resolution, registration, segmentation, etc.)
- quantitative fitting and image analysis
- anatomical visualization and analysis (patellar tilt, femoral cartilage thickness, etc.)

We hope that this open-source pipeline will be useful for quick anatomy/pathology analysis and will serve as a hub for adding support for analyzing different anatomies and scan sequences.

## Installation
DOSMA requires Python 3.6+. The core module depends on numpy, nibabel, nipype,
pandas, pydicom, scikit-image, scipy, PyYAML, and tqdm.

Additional AI features can be unlocked by installing tensorflow and keras. To
enable built-in registration functionality, download [elastix](https://elastix.lumc.nl/download.php).
Details can be found in the [setup documentation](https://dosma.readthedocs.io/en/latest/general/installation.html#setup).

To install DOSMA, run:

```bash
pip install dosma
```

If you would like to contribute to DOSMA, we recommend you clone the repository and
install DOSMA with `pip` in editable mode.

```bash
git clone git@github.com:ad12/DOSMA.git
cd DOSMA
pip install -e '.[dev]'
make dev
```

To run tests, build documentation and contribute, run
```bash
make autoformat test build-docs
```

## How to Cite
```
@inproceedings{desai2019dosma,
   Title={DOSMA: A deep-learning, open-source framework for musculoskeletal MRI analysis.},
   Author =  {Desai, Arjun D and Barbieri, Marco and Mazzoli, Valentina and Rubin, Elka and Black, Marianne S and Watkins, Lauren E and Gold, Garry E and Hargreaves, Brian A and Chaudhari, Akshay S},
   Booktitle={Proc. Intl. Soc. Mag. Reson. Med},
   Volume={27},
   Number={1106},
   Year={2019}
}
```

In addition to DOSMA, please also consider citing the work that introduced the method used for analysis.


