3 citations · 7 across the 4 of their papers we have counts for
5 papers · 1 filter
Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning
Mohammadamin Moradi, Runyu Jiang, Yingzi Liu +6
High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual treatment planning expertise. T…
Patient-Specific Deep Reinforcement Learning for Automatic Replanning in Head-and-Neck Cancer Proton Therapy
Malvern Madondo, Yuan Shao, Yingzi Liu +3
Anatomical changes during intensity-modulated proton therapy (IMPT) for head-and-neck cancer (HNC) can shift Bragg peaks, risking tumor underdosing and organ-at-risk overdosing. Tr…
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…
Intensity Non-uniformity Correction in MR Imaging Using Residual Cycle Generative Adversarial Network
Xianjin Dai, Yang Lei, Yingzi Liu +6
Purpose: Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue type is a crucial issue for quantitative MRI image analysis in daily clini…
Air, bone and soft-tissue Segmentation on 3D brain MRI Using Semantic Classification Random Forest with Auto-Context Model
Xue Dong, Yang Lei, Sibo Tian +7
As bone and air produce weak signals with conventional MR sequences, segmentation of these tissues particularly difficult in MRI. We propose to integrate patch-based anatomical sig…