15 citations · 28 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
X-ray Dissectography Enables Stereotography to Improve Diagnostic Performance
Chuang Niu, Ge Wang
X-ray imaging is the most popular medical imaging technology. While x-ray radiography is rather cost-effective, tissue structures are superimposed along the x-ray paths. On the oth…
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…
Physical Foundation for General Interior Tomography
Ge Wang
Gauge invariability guarantees the same form of the Maxwell equations in different coordinate systems, and is instrumental for electromagnetic cloaking to hide a region of interest…
First CT-MRI Scanner for Multi-dimensional Synchrony and Multi-physical Coupling
Ge Wang
We propose to prototype the first CT-MRI scanner for radiation therapy and basic research, demonstrate its transformative biomedical potential, and initiate a paradigm shift in mul…