This repository is for reproducing following paper about the BCD-NET approach to image reconstruction:
Hongki Lim, Il Yong Chun, Yuni Dewaraja, and Jeffrey Fessler: "Improved low-count quantitative PET reconstruction with an iterative neural network." IEEE Transactions on Medical Imaging, 39(11):3512-22, Nov. 2020.
To reproduce the paper, please make sure you have the following: Michigan Image Reconstruction Toolbox (MIRT) installed: http://web.eecs.umich.edu/~fessler/code/index.html.
Please download the digital phantom dataset shown in Fig. 2 via following link: https://drive.google.com/open?id=1VPcpI44LBNhKSYQ9EtMC6k-vTwDwRd_r
Modify paths in pcodes_init.m and train_matlab.py (l8th line) in mypcodes folder.
Then run main_recon_bcd_net_sca.m.