124 citations · 179 across the 5 of their papers we have counts for
5 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…
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…
A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy
Anjali Balagopal, Dan Nguyen, Howard Morgan +9
In post-operative radiotherapy for prostate cancer, the cancerous prostate gland has been surgically removed, so the clinical target volume (CTV) to be irradiated encompasses the m…
Intelligent Inverse Treatment Planning via Deep Reinforcement Learning, a Proof-of-Principle Study in High Dose-rate Brachytherapy for Cervical Cancer
Chenyang Shen, Yesenia Gonzalez, Peter Klages +6
Inverse treatment planning in radiation therapy is formulated as optimization problems. The objective function and constraints consist of multiple terms designed for different clin…
Intelligent Parameter Tuning in Optimization-based Iterative CT Reconstruction via Deep Reinforcement Learning
Chenyang Shen, Yesenia Gonzalez, Liyuan Chen +2
A number of image-processing problems can be formulated as optimization problems. The objective function typically contains several terms specifically designed for different purpos…