Author profile
Department of Radiation Oncology and Winship Cancer Institute, Emory University
Dose sparing of cardiac substructures has the potential to improve thoracic radiotherapy outcomes beyond conventional whole-heart dose-volume metrics. However, manual delineation of numerous substructures is prohibitive, limiting the availability of high-qual...
Multiparametric brain MRI is essential for delineating pediatric brain tumor subregions; however, long acquisition times often preclude complete multi-contrast imaging in pediatric patients, and large public pediatric lesion datasets remain limited. We propos...
This study aims to illuminate how HyperSight CBCT compares to conventional CBCT and planning CT in terms of radiomic features, applying statistical methods such as the Kruskal-Wallis H Test and the Intra-Class Correlation Coefficient (ICC).
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...
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...
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...
Accurate delineation of glioma substructures on multi-parametric MRI (mp-MRI) is critical for diagnosis, radiotherapy planning, and treatment response assessment. However, manual annotation of tumor subregions is labor-intensive and subject to inter-observer...
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...