325 citations · 1.6k across the 49 of their papers we have counts for
6 papers · 1 filter
Mining Domain Knowledge: Improved Framework towards Automatically Standardizing Anatomical Structure Nomenclature in Radiotherapy
Qiming Yang, Hongyang Chao, Dan Nguyen +1
The automatic standardization of nomenclature for anatomical structures in radiotherapy (RT) clinical data is a critical prerequisite for data curation and data-driven research in…
A Feasibility Study on Deep Learning-Based Radiotherapy Dose Calculation
Yixun Xing, Dan Nguyen, Weiguo Lu +2
Purpose: Various dose calculation algorithms are available for radiation therapy for cancer patients. However, these algorithms are faced with the tradeoff between efficiency and a…
Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy
Dan Nguyen, Rafe McBeth, Azar Sadeghnejad Barkousaraie +4
We propose a novel domain specific loss, which is a differentiable loss function based on the dose volume histogram, and combine it with an adversarial loss for the training of dee…
Generating Pareto optimal dose distributions for radiation therapy treatment planning
Dan Nguyen, Azar Sadeghnejad Barkousaraie, Chenyang Shen +2
Radiotherapy treatment planning currently requires many trail-and-error iterations between the planner and treatment planning system, as well as between the planner and physician f…
A Fast Deep Learning Approach for Beam Orientation Optimization for Prostate Cancer IMRT Treatments
Azar Sadeghnejad Barkousaraie, Olalekan Ogunmolu, Steve Jiang +1
We propose a fast beam orientation selection method, based on deep neural networks (DNN), capable of developing a plan comparable to those by the state-of-the-art column generation…
MRI-only brain radiotherapy: assessing the dosimetric accuracy of synthetic CT images generated using a deep learning approach
Samaneh Kazemifar, Sarah McGuire, Robert Timmerman +5
Purpose: This study assessed the dosimetric accuracy of synthetic CT images generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy, using a deep lea…