https://github.com/TorchIO-project/torchio
Medical imaging processing for deep learning.
https://github.com/TorchIO-project/torchio
augmentation data-augmentation deep-learning machine-learning medical-image-analysis medical-image-computing medical-image-processing medical-images medical-imaging-datasets medical-imaging-with-deep-learning python pytorch
Last synced: 11 days ago
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Medical imaging processing for deep learning.
- Host: GitHub
- URL: https://github.com/TorchIO-project/torchio
- Owner: TorchIO-project
- License: apache-2.0
- Created: 2019-11-26T09:10:09.000Z (about 6 years ago)
- Default Branch: main
- Last Pushed: 2025-01-30T22:39:21.000Z (12 months ago)
- Last Synced: 2025-01-30T23:01:37.808Z (12 months ago)
- Topics: augmentation, data-augmentation, deep-learning, machine-learning, medical-image-analysis, medical-image-computing, medical-image-processing, medical-images, medical-imaging-datasets, medical-imaging-with-deep-learning, python, pytorch
- Language: Python
- Homepage: https://torchio.org
- Size: 44.4 MB
- Stars: 2,119
- Watchers: 17
- Forks: 240
- Open Issues: 38
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.rst
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
> *Tools like TorchIO are a symptom of the maturation of medical AI research using deep learning techniques*.
Jack Clark, Policy Director
at [OpenAI](https://openai.com/) ([link](https://jack-clark.net/2020/03/17/)).
---
Package
CI
Code
Tutorials
Community
---
---
Original
Random blur
Random flip
Random noise
Random affine transformation
Random elastic transformation
Random bias field artifact
Random motion artifact
Random spike artifact
Random ghosting artifact
---
([Queue](https://torchio.readthedocs.io/patches/patch_training.html#queue)
for [patch-based training](https://torchio.readthedocs.io/patches/index.html))
---
TorchIO is a Python package containing a set of tools to efficiently
read, preprocess, sample, augment, and write 3D medical images in deep learning applications
written in [PyTorch](https://pytorch.org/),
including intensity and spatial transforms
for data augmentation and preprocessing.
Transforms include typical computer vision operations
such as random affine transformations and also domain-specific ones such as
simulation of intensity artifacts due to
[MRI magnetic field inhomogeneity](https://mriquestions.com/why-homogeneity.html)
or [k-space motion artifacts](http://proceedings.mlr.press/v102/shaw19a.html).
This package has been greatly inspired by NiftyNet,
[which is not actively maintained anymore](https://github.com/NifTK/NiftyNet/commit/935bf4334cd00fa9f9d50f6a95ddcbfdde4031e0).
## Credits
If you like this repository, please click on Star!
If you use this package for your research, please cite our paper:
[F. Pérez-García, R. Sparks, and S. Ourselin. *TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning*. Computer Methods and Programs in Biomedicine (June 2021), p. 106236. ISSN: 0169-2607.doi:10.1016/j.cmpb.2021.106236.](https://doi.org/10.1016/j.cmpb.2021.106236)
BibTeX entry:
```bibtex
@article{perez-garcia_torchio_2021,
title = {{TorchIO}: a {Python} library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning},
journal = {Computer Methods and Programs in Biomedicine},
pages = {106236},
year = {2021},
issn = {0169-2607},
doi = {https://doi.org/10.1016/j.cmpb.2021.106236},
url = {https://www.sciencedirect.com/science/article/pii/S0169260721003102},
author = {P{\'e}rez-Garc{\'i}a, Fernando and Sparks, Rachel and Ourselin, S{\'e}bastien},
}
```
This project is supported by the following institutions:
- [Engineering and Physical Sciences Research Council (EPSRC) & UK Research and Innovation (UKRI)](https://epsrc.ukri.org/)
- [EPSRC Centre for Doctoral Training in Intelligent, Integrated Imaging In Healthcare (i4health)](https://www.ucl.ac.uk/intelligent-imaging-healthcare/) (University College London)
- [Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS)](https://www.ucl.ac.uk/interventional-surgical-sciences/) (University College London)
- [School of Biomedical Engineering & Imaging Sciences (BMEIS)](https://www.kcl.ac.uk/bmeis) (King's College London)
## Getting started
See [Getting started](https://torchio.readthedocs.io/quickstart.html) for
[installation](https://torchio.readthedocs.io/quickstart.html#installation)
instructions
and a [Hello, World!](https://torchio.readthedocs.io/quickstart.html#hello-world)
example.
Longer usage examples can be found in the
[tutorials](https://github.com/TorchIO-project/torchio/blob/main/tutorials/README.md).
All the documentation is hosted on
[Read the Docs](http://torchio.rtfd.io/).
Please
[open a new issue](https://github.com/TorchIO-project/torchio/issues/new/choose)
if you think something is missing.
## Contributors
Thanks goes to all these people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
Fernando Pérez-García
💻 📖
valabregue
🤔 👀 💻 💬 🐛
GFabien
💻 👀 🤔
G.Reguig
💻
Niels Schurink
💻
Ibrahim Hadzic
🐛
ReubenDo
🤔
Julian Klug
🤔
David Völgyes
🤔 💻
Jean-Christophe Fillion-Robin
📖
Suraj Pai
🤔
Ben Darwin
🤔
Oeslle Lucena
🐛
Soumick Chatterjee
💻
neuronflow
📖
Jan Witowski
📖
Derk Mus
📖 💻 🐛
Christian Herz
🐛
Cory Efird
💻 🐛
Esteban Vaca C.
🐛
Ray Phan
🐛
Akis Linardos
🐛 💻
Nina Montana-Brown
📖 🚇
fabien-brulport
🐛
malteekj
🐛
Andres Diaz-Pinto
🐛
Sarthak Pati
📦 📖
GabriellaKamlish
🐛
Tyler Spears
🐛
DaGuT
📖
Xiangyu Zhao
🐛
siahuat0727
📖 🐛
Svdvoort
💻
Albans98
💻
Matthew T. Warkentin
💻
glupol
🐛
ramonemiliani93
📖 🐛 💻
Justus Schock
💻 🐛 🤔 👀
Stefan Milorad Radonjić
🐛
Sajan Gohil
🐛
Ikko Ashimine
📖
laynr
📖
Omar U. Espejel
🔊
James Butler
🐛
res191
🔍
nengwp
🐛 📖
susanveraclarke
🎨
nepersica
🐛
Sebastian Penhouet
🤔
Bigsealion
🐛
Dženan Zukić
👀
vasl12
✅ 🐛
François Rousseau
🐛
snavalm
💻
Jacob Reinhold
💻
Hsu
🐛
snipdome
🐛
SmallY
🐛
guigautier
🤔
AyedSamy
🐛
J. Miguel Valverde
🤔 💻 🐛
José Guilherme Almeida
🤔
Asim Usman
🐛
cbri92
🐛
Markus J. Ankenbrand
🐛
Ziv Yaniv
📖
Luca Lumetti
💻 📖
chagelo
🐛
mueller-franzes
💻 🐛
Abdelwahab Kawafi
🐛
Arthur Masson
🐛 📖
양현식
💻
nicoloesch
💻 🐛
Amund Vedal
📖
Alabamagan
🐛
sbdoherty
📖
Zhack47
🐛
Blake Dewey
📖
Doyeon Kim
🐛
KonoMaxi
🐛
Laurent Chauvin
🐛
Christian Hinge
🐛
zzz123xyz
🐛
Amin Alam
📖
marius-sm
🤔
haarisr
💻
Chris Winder
🐛
Ricky Walsh
💻
Keerthi Sravan Ravi
🐛
This project follows the
[all-contributors](https://github.com/all-contributors/all-contributors)
specification. Contributions of any kind welcome!