Metadata-Version: 2.1
Name: medreaders
Version: 1.0.4
Summary: Readers for medical imaging datasets
Home-page: https://github.com/ol-sen/medreaders
Author: Olga Senyukova
Author-email: olga.senyukova@graphics.cs.msu.ru
License: UNKNOWN
Description: # Readers for medical imaging datasets
        
        The goal of this project is to help researchers and practitioners working with medical imaging datasets to reduce an amount of routine work.
        
        The package contains the functions for reading a dataset into memory and for auxiliary tasks:
        * resizing images with their ground truth masks;
        * saving images and their ground truth masks slice by slice.
        
        In order to use this package you should download a dataset that you need from [Grand Challenges in Biomedical Image Analysis](https://grand-challenge.org/challenges/).
        
        First time the focus will be on datasets for cardiac image segmentation problem.
        
        Currently the package provides the means for working with [ACDC dataset](https://www.creatis.insa-lyon.fr/Challenge/acdc/index.html).
        
        ## Requirements
        
        * Python>=3.5
        
        ## Installation
        
        ```
        pip3 install medreaders
        ```
        
        ## Documentation
        
        Documentation is available at https://medreaders.readthedocs.io
        
        ## Project Structure
        ```
        .
        ├── docs
        │   ├── Makefile
        │   ├── conf.py
        │   ├── index.rst
        │   └── make.bat
        ├── medreaders
        │   ├── ACDC.py
        │   └── __init__.py
        ├── tests
        │   └── ACDC.py
        ├── .gitignore
        ├── LICENSE
        ├── README.md
        ├── requirements.txt
        └── setup.py
        
        3 directories, 12 files
        ```
        
        ## Corresponding Author
        
        * Olga Senyukova olga.senyukova@graphics.cs.msu.ru
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.5
Description-Content-Type: text/markdown
