Author profile
Department of Medical Physics, Memorial Sloan Kettering Cancer Center
We investigate the feasibility of using daily setup free-breathing cone-beam CT (CBCT) as a functional imaging modality to generate longitudinal ventilation maps throughout the treatment course, with the goal of detecting emerging lung function impairment dur...
An improved imager and software (HyperSight on a Varian TrueBeam linac) feature a larger detector panel and increase the maximum gantry rotation speed for CBCT imaging to 1.5 revolutions per minute (rpm). While enabling faster acquisition, its impact on free-...
Inferior CBCT quality from artifacts or incomplete data can compromise anatomy visualization during Image-Guided Radiotherapy (IGRT), increasing uncertainty in target localization and organ-at-risk positioning. Improving CBCT reconstruction can enable more re...
To develop a kV-triggered short-arc intrafraction motion monitoring technique for prostate SBRT VMAT by enabling on-treatment reconstruction of a 3D prostate and nearby organs-at-risk (OARs) volume within seconds. We propose an iterative short-arc CBCT recons...
Electronic portal imaging devices (EPID) are widely used clinically for patient-specific quality assurance (QA). Anticipating potential failures can help prioritize measurements to assess the need for plan revision and avoid downstream workflow disruptions. W...
This study proposes a transformer-based deep learning framework for markerless lung tumor tracking that improves localization accuracy, robustness, and computational efficiency of real-time intrafraction motion management for seamless clinical integration.
Markerless lung tumor tracking has the potential to reduce target margins and improve organ-at-risk (OAR) sparing during radiotherapy. We previously proposed a deep learning–based target decomposition approach for real-time markerless lung tumor tracking. Thi...