427 citations · 3.3k across the 77 of their papers we have counts for
7 papers · 1 filter
OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines
Aaron Babier, Rafid Mahmood, Binghao Zhang +56
We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients w…
MANAS: Multi-Scale and Multi-Level Neural Architecture Search for Low-Dose CT Denoising
Zexin Lu, Wenjun Xia, Yongqiang Huang +4
Lowering the radiation dose in computed tomography (CT) can greatly reduce the potential risk to public health. However, the reconstructed images from the dose-reduced CT or low-do…
Deep learning for accelerating Monte Carlo radiation transport simulation in intensity-modulated radiation therapy
Zhao Peng, Hongming Shan, Tianyu Liu +4
Cancer is a primary cause of morbidity and mortality worldwide. The radiotherapy plays a more and more important role in cancer treatment. In the radiotherapy, the dose distributio…
A Method of Rapid Quantification of Patient-Specific Organ Dose for CT Using Coupled Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing
Zhao Peng, Xi Fang, Pingkun Yan +7
Purpose: This paper describes a new method to apply deep-learning algorithms for automatic segmentation of radiosensitive organs from 3D tomographic CT images before computing orga…
Deep-learning-based Breast CT for Radiation Dose Reduction
Wenxiang Cong, Hongming Shan, Xiaohua Zhang +3
Cone-beam breast computed tomography (CT) provides true 3D breast images with isotropic resolution and high-contrast information, detecting calcifications as small as a few hundred…
Super-resolution MRI through Deep Learning
Qing Lyu, Chenyu You, Hongming Shan +1
Magnetic resonance imaging (MRI) is extensively used for diagnosis and image-guided therapeutics. Due to hardware, physical and physiological limitations, acquisition of high-resol…
A Synergized Pulsing-Imaging Network (SPIN)
Qing Lyu, Tao Xu, Hongming Shan +1
Currently, the deep neural network is the mainstream for machine learning, and being actively developed for biomedical imaging applications with an increasing emphasis on tomograph…