124 citations · 275 across the 11 of their papers we have counts for
11 papers
Experimental and Numerical Investigations on Robustness of a Deep Neural Network-based Multi-class Classification Model of CT Images with respect to Image Noise
Yuting Peng, Chenyang Shen, Yesenia Gonzalez +2
Robustness of Deep Neural Networks (DNNs) is an important aspect to consider for their clinical applications. This work examined robustness issue for a DNN-based multi-class classi…
Automatic Inverse Treatment Planning for Gamma Knife Radiosurgery via Deep Reinforcement Learning
Yingzi Liu, Chenyang Shen, Tonghe Wang +6
Purpose: Several inverse planning algorithms have been developed for Gamma Knife (GK) radiosurgery to determine a large number of plan parameters via solving an optimization proble…
Interactive Treatment Planning in High Dose-Rate Brachytherapy for Gynecological Cancer
Huan Liu, Chang M Ma, Xun Jia +3
High dose-rate brachytherapy (HDRBT) is widely used for gynecological cancer treatment. Although commercial treatment planning systems (TPSs) have inverse optimization modules, it…
Experimental and numerical studies on kV scattered x-ray imaging for real-time image guidance in radiation therapy
Yanqi Huang, Kai Yang, Youfang Lai +7
Motion management is a critical component of image guidance radiotherapy for lung cancer. We previously proposed a scheme using kV scattered x-ray photons for marker-less real-time…
Improving Efficiency of Training a Virtual Treatment Planner Network via Knowledge-guided Deep Reinforcement Learning for Intelligent Automatic Treatment Planning of Radiotherapy
Chenyang Shen, Liyuan Chen, Yesenia Gonzalez +1
We previously proposed an intelligent automatic treatment planning framework for radiotherapy, in which a virtual treatment planner network (VTPN) was built using deep reinforcemen…
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…