2 citations · 2 across the 6 of their papers we have counts for
7 papers · 1 filter
CBCT-Based Synthetic CT Generation Using Conditional Flow Matching Model
Junbo Peng, Huiqiao Xie, Tonghe Wang +2
Daily or weekly cone-beam computed tomography (CBCT) is employed in image-guided radiotherapy (IGRT) for precise patient alignment. However, its clinical utility in quantitative ta…
Dual-Energy Cone-Beam CT Using Two Orthogonal Projection Views: A Phantom Study
Junbo Peng, Tonghe Wang, Shaoyan Pan +1
This study proposes a novel imaging and reconstruction framework for dual-energy cone-beam CT (DECBCT) using only two orthogonal X-ray projections at different energy levels (2V-DE…
Patient-Specific CBCT Synthesis for Real-time Tumor Tracking in Surface-guided Radiotherapy
Shaoyan Pan, Vanessa Su, Junbo Peng +6
We present a new imaging system to support real-time tumor tracking for surface-guided radiotherapy (SGRT). SGRT uses optical surface imaging (OSI) to acquire real-time surface top…
Optimization-Based Image Reconstruction Regularized with Inter-Spectral Structural Similarity for Limited-Angle Dual-Energy Cone-Beam CT
Junbo Peng, Tonghe Wang, Huiqiao Xie +6
Background: Limited-angle (LA) dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without h…
Unsupervised Bayesian Generation of Synthetic CT from CBCT Using Patient-Specific Score-Based Prior
Junbo Peng, Yuan Gao, Chih-Wei Chang +7
Background: Cone-beam computed tomography (CBCT) scans, performed fractionally (e.g., daily or weekly), are widely utilized for patient alignment in the image-guided radiotherapy (…
Dual-Energy Cone-Beam CT Using Two Complementary Limited-Angle Scans with A Projection-Consistent Diffusion Model
Junbo Peng, Chih-Wei Chang, Richard L. J. Qiu +5
Background: Dual-energy imaging on cone-beam CT (CBCT) scanners has great potential in different clinical applications, including image-guided surgery and adaptive proton therapy.…
Image-Domain Material Decomposition for Dual-energy CT using Unsupervised Learning with Data-fidelity Loss
Junbo Peng, Chih-Wei Chang, Huiqiao Xie +6
Background: Dual-energy CT (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise…