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...
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...
Online adaptive proton therapy is highly sensitive to interfractional anatomical variation, yet conventional online replanning workflows remain time‑intensive and limit routine clinical implementation, particularly for hypofractionated prostate stereotactic b...
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...