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BCD_Net
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BCD_Net
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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.](http://doi.org/10.1109/TMI.2020.2998480) [arXiv version of paper.](https://arxiv.org/abs/1906.02327) ## Setting up and Reproducing 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`.
