56 citations · 58 across the 5 of their papers we have counts for
5 papers
Feasibility of a General-Purpose Deep Learning Dose Engine: A Multi-Site Validation Study
Yao Zhao, Ka Ho Tam, Raphael Douglas +6
Conventional radiotherapy dose calculation algorithms are often computationally slow and non-differentiable, creating bottlenecks for online adaptive radiotherapy (ART) and limitin…
Automated WBRT Treatment Planning via Deep Learning Auto-Contouring and Customizable Landmark-Based Field Aperture Design
Yao Xiao, Carlos Cardenas, Dong Joo Rhee +12
In this work, we developed and evaluated a novel pipeline consisting of two landmark-based field aperture generation approaches for WBRT treatment planning; they are fully automate…
Automation of Radiation Treatment Planning for Rectal Cancer
Kai Huang, Prajnan Das, Adenike M. Olanrewaju +9
To develop an automated workflow for rectal cancer three-dimensional conformal radiotherapy treatment planning that combines deep-learning(DL) aperture predictions and forward-plan…
OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines
Aaron Babier, Rafid Mahmood, Binghao Zhang +56
We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients w…
Effects of the difference in tube voltage of the CT scanner on dose calculation
Dong Joo Rhee, Sung-woo Kim, Young Min Moon +2
Computed Tomography (CT) measures the attenuation coefficient of an object and converts the value assigned to each voxel into a CT number. In radiation therapy, CT number, which is…