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…
Comparison of projection domain, image domain, and comprehensive deep learning for sparse-view X-ray CT image reconstruction
Kaichao Liang, Hongkai Yang, Yuxiang Xing
X-ray Computed Tomography (CT) imaging has been widely used in clinical diagnosis, non-destructive examination, and public safety inspection. Sparse-view (sparse view) CT has great…