https://github.com/sudohainguyen/stan-small-tumor-aware-network
Unofficial implementation of STAN paper published at ISBI 2020 by researchers from University of Idaho using Tensorflow Keras 2.0.
https://github.com/sudohainguyen/stan-small-tumor-aware-network
implementation-of-research-paper semantic-segmentation stan stan-paper tensorflow2
Last synced: 5 months ago
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Unofficial implementation of STAN paper published at ISBI 2020 by researchers from University of Idaho using Tensorflow Keras 2.0.
- Host: GitHub
- URL: https://github.com/sudohainguyen/stan-small-tumor-aware-network
- Owner: sudohainguyen
- License: mit
- Created: 2020-04-18T10:06:36.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-06-08T01:16:58.000Z (over 5 years ago)
- Last Synced: 2025-03-25T15:15:07.015Z (7 months ago)
- Topics: implementation-of-research-paper, semantic-segmentation, stan, stan-paper, tensorflow2
- Language: Python
- Homepage:
- Size: 2.92 MB
- Stars: 12
- Watchers: 3
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# STAN - Small Tumor-aware Network
Unofficial implementation of [STAN paper](https://arxiv.org/pdf/2002.01034.pdf) published at ISBI 2020 by authors from University of Idaho using Tensorflow 2.0.
STAN architecture
## Dataset
We use the [Dataset B](https://arxiv.org/pdf/1801.03182.pdf) in this implementation. Access permission needed, visit the [Release Requirement](http://www2.docm.mmu.ac.uk/STAFF/m.yap/files/BUS_ReleaseAgreement.pdf) for more details.
## TODOs
- [x] Dataset B Generator
- [x] Model implementation
- [x] Training code using `click`
- [x] Example for Dataset B
- [x] Tversky loss function
- [x] Dice loss function
- [ ] Lovasz loss function
- [ ] Focal loss function
- [ ] Smarter training procedure with `mlflow` and `hydra`
- [ ] Inference code
- [ ] Evaluate code