Self-adaptive weight embedded lightweight network using semi-supervised learning for low-dose CT image denoising
Dataset preparation：train, val, test
Training: Please set "mode" is train, then change "train_path" and "validata_path" to your train path and val path.
Testing: Please set "mode" is test, then change "train_path" to your test path, and then set "test_iters".
Please note the setting of data names in loader.py when executing SWELNet-main.
Paper Citation: J. Wang et al., "Self-Adaptive Weight Embedded Lightweight Network Using Semi-Supervised Learning for Low-Dose CT Image Denoising," in IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 9, no. 7, pp. 890-904, Sept. 2025, doi: 10.1109/TRPMS.2025.3541169.