Author profile
Department of Radiation Oncology and Winship Cancer Institute, Emory University
Foundation models (FMs) have demonstrated strong performance on challenging radiation therapy tasks such as automatic delineation, deformable image registration, and multimodal visual question answering (VQA). However, they are typically task-specific and req...
High-resolution CT is important for radiotherapy contouring and dose calculation. However, acquiring high through-plane resolution is often constrained by radiation dose, motion artifacts, and scanner limitations. This study aims to generate high-resolution (...
Radiomics-enabled adaptive radiotherapy depends on on-treatment imaging that maintains CT-like quantitative biomarkers. We evaluated whether HyperSight CBCT preserves planning-CT radiomic biomarkers more faithfully than conventional CBCT in pelvic radiotherap...
To test whether HyperSight CBCT (HS-CBCT) improves consistency of longitudinal radiomics with planning CT versus conventional CBCT in pelvic radiotherapy.
Deformable image registration (DIR) in medical imaging remains inherently ill-conditioned due to structural ambiguities and weak anatomical constraints. Although foundation models (FMs) have shown strong promise for unsupervised DIR, existing approaches typic...
Low-count PET acquisition and inter-radiotracer translation offer effective strategies to reduce radiation dose and mitigate tracer availability constraints. Recent self-supervised learning (SSL) foundation models (e.g., DINOv3) have demonstrated strong abili...
Prostate MRI is increasingly used in modern radiotherapy, but compared with CT, large-scale MRI datasets remain limited for fine-tuning foundation models. This study investigates the cross-modality transferability of a CT–fine-tuned foundation model to prosta...