Author profile
Department of Medical Biophysics, University of Toronto
To assess dose calculation accuracy on cone-beam computed tomography (CBCT) images relative to the RayStation CBCT correction framework (CBCTcorr) across multiple CBCT platforms, anatomical sites, and clinical scenarios.
To expedite the diagnosis-to-treatment workflow in radiation oncology, this work evaluates a machine learning approach for generating synthetic radiation therapy (RT) planning images directly from diagnostic computed tomography (CT) images, potentially elimin...
To develop a 3D unified deep learning model for predicting dose distribution of various sites and protocols by conditioning the model using text-embedding representation for each protocol.
Artificial intelligence (AI) is moving rapidly into medical imaging workflows, yet questions remain about whether these tools can truly be considered dependable and trustworthy in clinical practice. This session will address three critical dimensions: technic...
Peer review is a critical quality assurance step in radiation therapy (RT), but not all cases require the same level of attention. We aimed to develop a machine learning (ML) tool to help prioritize breast RT plans for peer review based on their likelihood of...