The official code for "Inter-Scale Dependency Modeling for Skin Lesion Segmentation with Transformer-based Networks".
- 1 May., 2023 : Initial release.
- 28 Apr., 2023: Accepted.
- 7 Apr., 2023: Submitted to MIDL 2023 [
Under Review].
@inproceedings{eskandari2023interscale,
title={Inter-Scale Dependency Modeling for Skin Lesion Segmentation with Transformer-based Networks},
author={Sania Eskandari and Janet Lumpp},
booktitle={Medical Imaging with Deep Learning, short paper track},
year={2023},
url={https://openreview.net/forum?id=JExQEfV5um}
}
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In order to run the code and experiments, you need to first install the dependencies and then download and move the data to the right directory.
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For ISIC 2017-18 datasets, we used the ISIC Challenge datasets link.
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Run the following code to install the Requirements.
pip install -r requirements.txt
You can download the learned weights of the DAEFormer in the following table.
Task | Dataset | Learned weights |
---|---|---|
Skin Lesion Segmentation | ISIC 2017 | ISCF |
Skin Lesion Segmentation | ISIC 2018 | ISCF |
This repo heavily built on the following repos.