666 citations · 918 across the 43 of their papers we have counts for
30 papers · 1 filter
One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy
Shaoyan Pan, Kirk Jon Luca, Yuan Gao +8
In this work, we introduce the One-for-All Adaptive Radiotherapy Planning Agent, a unified foundation-model-based system that performs complete, treatment-specific online adaptive…
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…
Low-Dose CT Imaging Using a Regularization-Enhanced Efficient Diffusion Probabilistic Model
Qiang Li, Mojtaba Safari, Shansong Wang +4
Low-dose computed tomography (LDCT) reduces patient radiation exposure but introduces substantial noise that degrades image quality and hinders diagnostic accuracy. Existing denois…
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…
A Review of Artificial Intelligence in Brachytherapy
Jingchu Chen, Richard Qiu, Tonghe Wang +2
Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine l…
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.…
High-resolution 3T to 7T MRI Synthesis with a Hybrid CNN-Transformer Model
Zach Eidex, Jing Wang, Mojtaba Safari +6
7 Tesla (7T) apparent diffusion coefficient (ADC) maps derived from diffusion-weighted imaging (DWI) demonstrate improved image quality and spatial resolution over 3 Tesla (3T) ADC…
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…
One-step Iterative Estimation of Effective Atomic Number and Electron Density for Dual Energy CT
Qian Wang, Huiqiao Xie, Tonghe Wang +7
Dual-energy computed tomography (DECT) is a promising technology that has shown a number of clinical advantages over conventional X-ray CT, such as improved material identification…
Hippocampus Substructure Segmentation Using Morphological Vision Transformer Learning
Yang Lei, Yifu Ding, Richard L. J. Qiu +6
Background: The hippocampus plays a crucial role in memory and cognition. Because of the associated toxicity from whole brain radiotherapy, more advanced treatment planning techniq…
Data-Driven Volumetric Image Generation from Surface Structures using a Patient-Specific Deep Leaning Model
Shaoyan Pan, Chih-Wei Chang, Marian Axente +5
The advent of computed tomography significantly improves patient health regarding diagnosis, prognosis, and treatment planning and verification. However, tomographic imaging escala…
Deep Learning in MRI-guided Radiation Therapy: A Systematic Review
Zach Eidex, Yifu Ding, Jing Wang +5
MRI-guided radiation therapy (MRgRT) offers a precise and adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematic…
CBCT-Based Synthetic CT Image Generation Using Conditional Denoising Diffusion Probabilistic Model
Junbo Peng, Richard L. J. Qiu, Jacob F Wynne +8
Background: Daily or weekly cone-beam computed tomography (CBCT) scans are commonly used for accurate patient positioning during the image-guided radiotherapy (IGRT) process, makin…
Early in vivo Radiation Damage Quantification for Pediatric Craniospinal Irradiation Using Longitudinal MRI for Intensity Modulated Proton Therapy
Chih-Wei Chang, Matt Goette, Nadja Kadom +8
Purpose: Proton vertebral body sparing craniospinal irradiation (VBS CSI) treats the thecal sac while avoiding the anterior vertebral bodies in effort to reduce myelosuppression an…
Deep learning-based Fast Volumetric Image Generation for Image-guided Proton FLASH Radiotherapy
Chih-Wei Chang, Yang Lei, Tonghe Wang +7
Proton FLASH therapy leverages ultra-high dose-rate radiation to enhance the sparing of organs at risk without compromising tumor control probability. To prepare for the delivery o…
Automatic Inverse Treatment Planning for Gamma Knife Radiosurgery via Deep Reinforcement Learning
Yingzi Liu, Chenyang Shen, Tonghe Wang +6
Purpose: Several inverse planning algorithms have been developed for Gamma Knife (GK) radiosurgery to determine a large number of plan parameters via solving an optimization proble…
Generative Adversarial Network for Image Synthesis
Yang Lei, Richard L. J. Qiu, Tonghe Wang +3
This chapter reviews recent developments of generative adversarial networks (GAN)-based methods for medical and biomedical image synthesis tasks. These methods are classified into…
Synthetic MRI-aided Head-and-Neck Organs-at-Risk Auto-Delineation for CBCT-guided Adaptive Radiotherapy
Xianjin Dai, Yang Lei, Tonghe Wang +7
Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-va…
An institutional study on plan quality and variation of manual forward planning for Gamma Knife radiosurgery for vestibular schwannoma
Zhen Tian, Tonghe Wang, Xiaofeng Yang +5
Due to the complexity and cumbersomeness of Gamma Knife (GK) manual forward planning, the quality of the resulting treatment plans heavily depends on the planners skill, experience…
A plan quality control method of treatment planning for Gamma Knife radiosurgery
Tonghe Wang, Matt D. Giles, Elizabeth Butker +5
With many variables to adjust, conventional manual forward planning for Gamma Knife (GK) radiosurgery is very complicated and cumbersome. The resulting plan quality heavily depends…
Learning-Based Synthetic Dual Energy CT Imaging from Single Energy CT for Stopping Power Ratio Calculation in Proton Radiation Therapy
Serdar Charyyev, Tonghe Wang, Yang Lei +7
Purpose: Dual-energy CT (DECT) has been shown to derive stopping power ratio (SPR) map with higher accuracy than conventional single energy CT (SECT) by obtaining the energy depend…