Author profile
Department of Radiation Oncology and Winship Cancer Institute, Emory University
Accurate auto-contouring is essential for efficient prostate radiotherapy, particularly in image-guided and adaptive workflows, where contour quality influences clinical decision-making. This study quantitatively evaluates Radformation auto-contouring perform...
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...
Cone-beam CT (CBCT) is integral to modern radiotherapy workflows; however, limited soft-tissue contrast and imaging artifacts restrict its quantitative use, particularly for online auto-segmentation in CBCT-guided adaptive radiotherapy. Models pretrained on c...
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...
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...