https://github.com/justusschock/medical-data

Helpful utilities for deep learning in medical image analysis/medical image computing
https://github.com/justusschock/medical-data

deep-learning medical-imaging pytorch pytorch-lightning

Last synced: 3 months ago
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Helpful utilities for deep learning in medical image analysis/medical image computing

• Host: GitHub
• URL: https://github.com/justusschock/medical-data
• Owner: justusschock
• License: apache-2.0
• Created: 2021-08-16T08:27:41.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-07-02T00:35:19.000Z (7 months ago)
• Last Synced: 2024-10-02T11:37:40.648Z (4 months ago)
• Topics: deep-learning, medical-imaging, pytorch, pytorch-lightning
• Language: Python
• Homepage:
• Size: 232 KB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# Medical Data

[![UnitTest](https://github.com/justusschock/medical-data/actions/workflows/unittests.yaml/badge.svg)](https://github.com/justusschock/medicaldata/actions/workflows/unittests.yaml) [![Build Package](https://github.com/justusschock/medical-data/actions/workflows/package_build.yaml/badge.svg)](https://github.com/justusschock/medical-data/actions/workflows/package_build.yaml) ![PyPI](https://img.shields.io/pypi/v/medical-data?color=grene) [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/justusschock/medical-data/main.svg)](https://results.pre-commit.ci/latest/github/justusschock/medical-data/main)

This repository contains utilities for handling data in medical image analysis that are not specific to certain tasks.

So far it consists of 2 major parts:

An abstract Dataset API built on top of `torch.utils.data.Dataset` and `torchio.data.Subject` as well as general transforms for this kind of data.

To use the dataset classes, you basically only need to implement the `parse_subjects` method to return a list of samples and everything else will work automatically.

You will automatically get image statistics such as median spacing or median shape. For label statistics, you either need to subclass the `AbstractDiscreteLabelDataset` or implement the `get_single_label_stats` and `aggregate_label_stats` methods.

All transforms work on `torchio.data.Subjects` and can be passed to the datasets as optional parameters. You can also pass `"default"` as a parameter to use the default transforms.

Pull requests for other common utilities are highly welcomed.

## Installation

This project can be installed either from PyPI or by cloning the repository from GitHub.

For an install of published packages, use the command

```bash

    pip install medical-data

```

To install from the (cloned) repository, use the command

```bash

    pip install PATH/TO/medical-data

```

You can also add `-e` to the command to make an editable install in case you want to modify the code.

You can also install the package directly from GitHub by running

```bash

    pip install git+https://github.com/justusschock/medical-data.git

```