6 citations · 6 across the 5 of their papers we have counts for
8 papers
Personalising Deformable Image Registration with Clinical Context and Deformation History for Adaptive Radiotherapy
Caiwen Jiang, Songlin Zhao, Yuzhen Ding +23
Adaptive radiotherapy must account for anatomical changes during treatment, but doing so depends on reliably mapping targets, organs at risk and dose across serial images. Existing…
A Multimodal Clinically Informed Coarse-to-Fine Framework for Longitudinal CT Registration in Proton Therapy
Caiwen Jiang, Yuzhen Ding, Mi Jia +14
Proton therapy offers superior organ-at-risk sparing but is highly sensitive to anatomical changes, making accurate deformable image registration (DIR) across longitudinal CT scans…
An Automated Retrieval-Augmented Generation LLaMA-4 109B-based System for Evaluating Radiotherapy Treatment Plans
Junjie Cui, Peilong Wang, Jason Holmes +15
Purpose: To develop a retrieval-augmented generation (RAG) system powered by LLaMA-4 109B for automated, protocol-aware, and interpretable evaluation of radiotherapy treatment plan…
Diffusion Transformer-based Universal Dose Denoising for Pencil Beam Scanning Proton Therapy
Yuzhen Ding, Jason Holmes, Hongying Feng +13
Purpose: Intensity-modulated proton therapy (IMPT) offers precise tumor coverage while sparing organs at risk (OARs) in head and neck (H&N) cancer. However, its sensitivity to anat…
Accurate Patient Alignment without Unnecessary Imaging Dose via Synthesizing Patient-specific 3D CT Images from 2D kV Images
Yuzhen Ding, Jason M. Holmes, Hongying Feng +8
In radiotherapy, 2D orthogonally projected kV images are used for patient alignment when 3D-on-board imaging(OBI) unavailable. But tumor visibility is constrained due to the projec…
Noisy probing dose facilitated dose prediction for pencil beam scanning proton therapy: physics enhances generalizability
Lian Zhang, Jason M. Holmes, Zhengliang Liu +11
Purpose: Prior AI-based dose prediction studies in photon and proton therapy often neglect underlying physics, limiting their generalizability to handle outlier clinical cases, esp…
Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 report
Jason Holmes, Lian Zhang, Yuzhen Ding +7
Purpose: To introduce the concept of using large language models (LLMs) to re-label structure names in accordance with the American Association of Physicists in Medicine (AAPM) Tas…
Modelling small block aperture in an in-house developed GPU-accelerated Monte Carlo-based dose engine for pencil beam scanning proton therapy
Hongying Feng, Jason M. Holmes, Sujay A. Vora +8
Purpose: To enhance an in-house graphic-processing-unit (GPU) accelerated virtual particle (VP)-based Monte Carlo (MC) proton dose engine (VPMC) to model aperture blocks in both do…