4 citations · 5 across the 2 of their papers we have counts for
3 papers
eess.IV2020
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model
Zhuonan He, Yikun Zhang, Yu Guan +4
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in clinical applications. Iterative reconstruction is one of the most promising ways to compen…
physics.med-ph2020★ 1 cited
DIRECT-Net: a unified mutual-domain material decomposition network for quantitative dual-energy CT imaging
Ting Su, Xindong Sun, Yikun Zhang +7
By acquiring two sets of tomographic measurements at distinct X-ray spectra, the dual-energy CT (DECT) enables quantitative material-specific imaging. However, the conventionally d…
physics.med-ph2020★ 4 cited
Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network
Tianling Lyu, Zhan Wu, Yikun Zhang +3
Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are…