This project hosts the codes for the implementation of the paper Bounding Box Tightness Prior for Weakly Supervised Image Segmentation (MICCAI 2021) [miccai] [arxiv].
Download Promise12 dataset, and put it on the "data/prostate" folder.
Download Atlas dataset, and put it on the "data/atlas" folder.
Run the following codes for preprocessing:
# trainig and valid subsets for promise12 dataset
python preprocess/slice_promise_train_val.py
python preprocess/slice_promise_augment_train_val.py
# trainig and valid subsets for atlas dataset
python preprocess/slice_atlas.py
# The following experiments include full supervision (exp_no=0), MIL ablation study (exp_no=1), smooth maximum approximation ablation study (exp_no=2,3), and main experiments (exp_no=4,5)
# training for promise12 dataset, exp_no=0,1,2,3,4,5
CUDA_VISIBLE_DEVICES=0 python tools/train_promise_unetwithbox.py --n_exp exp_no
# training for atlas dataset, exp_no=0,1,2,3,4,5
CUDA_VISIBLE_DEVICES=0 python tools/train_atlas_unetwithbox.py --n_exp exp_no
# Dice validation results for promise12 dataset, exp_no=0,1,2,...,16
CUDA_VISIBLE_DEVICES=0 python tools/valid_promise_unetwithbox.py --n_exp exp_no
# Dice validation results for atlas dataset, exp_no=0,1,2,...,16
CUDA_VISIBLE_DEVICES=0 python tools/valid_atlas_unetwithbox.py --n_exp exp_no
python tools/report_promise_unetwithbox_paper.py
python tools/report_atlas_unetwithbox_paper.py
Please consider citing our paper in your publications if the project helps your research.
@inproceedings{wang2021bounding,
title={Bounding Box Tightness Prior for Weakly Supervised Image Segmentation},
author={Wang, Juan and Xia, Bin},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={526--536},
year={2021},
organization={Springer}
}
- 3/16/2022: a bug in _C_promise.py was fixed such that the training subset was used for training.
- 3/17/2022: add data augmentation script for promise12 dataset