dosma 0.0.12

An AI-powered open-source medical image analysis toolbox

DOSMA: Deep Open-Source Medical Image Analysis

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 from MRI and will serve as a hub for adding support for analyzing different anatomies and scan sequences.

Documentation | Questionnaire

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. Details can be found in the setup documentation.

To install DOSMA, run:

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.

git clone [e-mail]:ad12/DOSMA.git
cd DOSMA
pip install -e '.[dev]'
make dev

To run tests, build documentation and contribute, run

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.