2 citations · 6 across the 5 of their papers we have counts for
6 papers
Extraction-based Deep Learning Reconstruction of Interior Tomography
Changyu Chen, Yuxiang Xing, Li Zhang +1
Interior tomography is a typical strategy for radiation dose reduction in computed tomography, where only a certain region-of-interest (ROI) is scanned. However, given the truncate…
A novel deep learning-based method for monochromatic image synthesis from spectral CT using photon-counting detectors
Ao Zheng, Hongkai Yang, Li Zhang +1
With the growing technology of photon-counting detectors (PCD), spectral CT is a widely concerned topic which has the potential of material differentiation. However, due to some no…
Truncated analytic moment analysis and its hybrid-field contrast in grating-based x-ray phase contrast imaging
Chengpeng Wu, Li Zhang, Xinbin Li +4
For grating-based x-ray phase contrast imaging (GPCI), a multi-order moment analysis (MMA) has been recently developed to obtain multiple contrasts from the ultra-small-angle x-ray…
A cascaded dual-domain deep learning reconstruction method for sparsely spaced multidetector helical CT
Ao Zheng, Hewei Gao, Li Zhang +1
Helical CT has been widely used in clinical diagnosis. Sparsely spaced multidetector in z direction can increase the coverage of the detector provided limited detector rows. It can…
A Model-based Deep Learning Reconstruction for X-ray CT
Kaichao Liang, Li Zhang, Yirong Yang +2
Low dose CT is of great interest in these days. Dose reduction raises noise level in projections and decrease image quality in reconstructions. Model based image reconstruction can…
Unsupervised Learnable Sinogram Inpainting Network (SIN) for Limited Angle CT reconstruction
Ji Zhao, Zhiqiang Chen, Li Zhang +1
In this paper, we propose a sinogram inpainting network (SIN) to solve limited-angle CT reconstruction problem, which is a very challenging ill-posed issue and of great interest fo…