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.
First time the focus will be on datasets for cardiac image segmentation problem.
Currently the package provides the means for working with ACDC dataset.
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
1 maintainer
Metadata
1 maintainer
Release files for medreaders 1.0.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| medreaders-1.0.8.tar.gz | 9.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| medreaders-1.0.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.6 kB
Release files / medreaders-1.0.8.tar.gz
| Download URL | medreaders-1.0.8.tar.gz |
|---|---|
| Size | 9.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / medreaders-1.0.8-py3-none-any.whl
| Download URL | medreaders-1.0.8-py3-none-any.whl |
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| Size | 9.2 kB |
| Tags | Python 3 |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/57.0.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.9
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