Official Pytorch implementation of "Patch-wise Deep Metric Learning for Unsupervised Low-Dose CT Denoising" (MICCAI 2022)
Chanyong Jung, Joonhyung Lee, Sunkyoung You, Jong Chul Ye
Link: https://arxiv.org/abs/2207.02377
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We provide the source code for AAPM dataset.
(2016 NIH-AAPM-Mayo Clinic Low Dose CT Grand Challenge dataset)
We randomly select 3112 images for train set, 421 images for validation set.
421 images are used for test set. -
Refer the following code to obtain the model:
python main.py --prj_name [folder-name] --log_name [log-file-name] \
--dataset_name AAPM --data_root [path-to-data] --gpu_ids 0
Our source code is based on the official implementation of CUT.