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20172023
most citedIntelligent Parameter Tuning in Optimization-based Iterative CT Reconstruction via Deep Reinforcement Learning

7 citations · 7 across the 1 of their papers we have counts for

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physics.med-ph2018

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…

physics.med-ph2018

Generating Synthesized Computed Tomography (CT) from Cone-Beam Computed Tomography (CBCT) using CycleGAN for Adaptive Radiation Therapy

Xiao Liang, Liyuan Chen, Dan Nguyen +5

Cone beam computed tomography (CBCT) images can be used for dose calculation in adaptive radiation therapy (ART). The main challenges are the large artefacts and inaccurate Hounsfi…

physics.med-ph2018

Combining Many-objective Radiomics and 3-dimensional Convolutional Neural Network through Evidential Reasoning to Predict Lymph Node Metastasis in Head and Neck Cancer

Liyuan Chen, Zhiguo Zhou, David Sher +5

Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential for treatment optimizati…

physics.med-ph2018

Deriving ventilation imaging from 4DCT by deep convolutional neural network

Yuncheng Zhong, Yevgeniy Vinogradskiy, Liyuan Chen +6

Purpose: Functional imaging is emerging as an important tool for lung cancer treatment planning and evaluation. Compared with traditional methods such as nuclear medicine ventilati…

physics.med-ph2018

Predicting Lymph Node Metastasis in Head and Neck Cancer by Combining Many-objective Radiomics and 3-dimensioal Convolutional Neural Network through Evidential Reasoning

Zhiguo Zhou, Liyuan Chen, David Sher +5

Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential for treatment optimizati…

physics.med-ph20177 cited

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…