https://github.com/marrlab/instantdl
InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
https://github.com/marrlab/instantdl
classification deep-learning docker gpu image-segmentation instance-segmentation pixel-wise-regression regression semantic-segmentation
Last synced: over 1 year ago
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InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
- Host: GitHub
- URL: https://github.com/marrlab/instantdl
- Owner: marrlab
- License: mit
- Created: 2020-03-11T08:53:40.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-03-24T22:25:51.000Z (over 3 years ago)
- Last Synced: 2025-03-13T15:40:17.456Z (over 1 year ago)
- Topics: classification, deep-learning, docker, gpu, image-segmentation, instance-segmentation, pixel-wise-regression, regression, semantic-segmentation
- Language: Python
- Homepage: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04037-3
- Size: 126 MB
- Stars: 43
- Watchers: 4
- Forks: 8
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# InstandDL: An easy and convenient deep learning pipeline for image segmentation and classification
[](https://travis-ci.com/marrlab/InstantDL)
InstantDL enables experts and non-experts to use state-of-the art deep learning methods on biomedical image data. InstantDL offers the four most common tasks in medical image processing: Semantic segmentation, instance segmentation, pixel-wise regression and classification. For more in depth discussion on the methods, as well as comparing the results and bechmarks using this package, please refer to our preprint on bioRxiv [here](https://doi.org/10.1101/2020.06.22.164103)
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## Documentation
For documentation please refere to [docs](docs)
For a short video introducing InstantDL please see:
## Contributing
We are happy about any contributions. For any suggested changes, please send a pull request to the *develop* branch.
## Citation
If you use InstantDL, please cite this paper:
```
@article {
author = {Waibel, Dominik Jens Elias and Shetab Boushehri, Sayedali and Marr, Carsten},
title = {InstantDL - An easy-to-use deep learning pipeline for image segmentation and classification},
year = {2021},
doi = {10.1186/s12859-021-04037-3},
URL = {https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04037-3#article-info},
eprint = {https://doi.org/10.1186/s12859-021-04037-3},
journal = {BMC Bioinformatics}
}
```
