16 citations · 31 across the 10 of their papers we have counts for
6 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…
A Digital Twin Framework for Adaptive Treatment Planning in Radiotherapy
Chih-Wei Chang, Sri Sai Akkineni, Mingzhe Hu +7
The development of a digital twin (DT) framework for fast online adaptive proton therapy planning in prostate stereotactic body radiation therapy (SBRT) with dominant intraprostati…
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…
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 (…
MRI-based Material Mass Density and Relative Stopping Power Estimation via Deep Learning for Proton Therapy
Yuan Gao, Chih-Wei Chang, Sagar Mandava +10
Magnetic Resonance Imaging (MRI) is increasingly incorporated into treatment planning, because of its superior soft tissue contrast used for tumor and soft tissue delineation versu…
Multimodal Imaging-based Material Mass Density Estimation for Proton Therapy Using Physics-Constrained Deep Learning
Chih-Wei Chang, Raanan Marants, Yuan Gao +7
Mapping computed tomography (CT) number to material property dominates the proton range uncertainty. This work aims to develop a physics-constrained deep learning-based multimodal…