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physics.med-ph2023
Noise suppression in photon-counting CT using unsupervised Poisson flow generative models
Dennis Hein, Staffan Holmin, Timothy Szczykutowicz +4
Deep learning has proven to be important for CT image denoising. However, such models are usually trained under supervision, requiring paired data that may be difficult to obtain i…
physics.med-ph2018
A Synergized Pulsing-Imaging Network (SPIN)
Qing Lyu, Tao Xu, Hongming Shan +1
Currently, the deep neural network is the mainstream for machine learning, and being actively developed for biomedical imaging applications with an increasing emphasis on tomograph…