Keywords: Unsupervised Segmentation, OCT, Scale-invariant.
Source code of "Multiscale Unsupervised Retinal Edema Area Segmentation in OCT Images (MICCAI2022)".
- Download
ai_challenger_fl2018dataset from ai challenge. - Run below
cd pprocess
# change the varibale `adjust_to` and `new_size` to 96
# and get the dataset with image size 96x96
python make_edema.py
# split the train-test
python split_edema.py
# change the varibale `adjust_to` and `new_size` to 256
# and get the dataset with image size 256x256
python make_edema.py
# reuse the split file in Edema96 dataset./train.sh@inproceedings{yuan2022multiscale,
title={Multiscale Unsupervised Retinal Edema Area Segmentation in OCT Images},
author={Yuan, Wenguang and Lu, Donghuan and Wei, Dong and Ning, Munan and Zheng, Yefeng},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={667--676},
year={2022},
organization={Springer}
}
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