Search Submissions 🔎

Results for "gpu acceleration": 4 found

A GPU Accelerated Monte Carlo Dose Engine for Small Animal Proton Radiotherapy

Authors: Haonian Gong, Yue Gu, Meiqi Liu, Zihao Liu, Hsiao-Ming Lu, Yuxiang Wang, Yidong Yang, Cheng Zheng

Affiliation: Hefei Ion Medical Center, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Department of Engineering and Applied Physics, University of Science and Technology of China, University of Science and Technology of China

Abstract Preview: Purpose:
Proton radiotherapy in preclinical small animals requires specific dose engine due to its low energy and small irradiation volume. This study is to develop a GPU-based Monte Carlo dose eng...

GPU-Accelerated Beamlet and Full Dose Calculations for Efficient Radiation Therapy Planning

Authors: Girish Bal, Jan Kralj, Ayan Mitra, PhD, Ling Shao, Matjaz Subic, Yevgen Voronenko

Affiliation: RefleXion Medical, Cosylab

Abstract Preview: Purpose: This work enhances the efficiency of radiation therapy treatment planning by optimizing the beamlet dose matrix and full patient dose computations using GPU acceleration. The Collapsed-Cone C...

Quality and Performance Advantages of a Machine Learning-Assisted Framework for IMRT Fluence Map Optimization

Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang

Affiliation: Duke University Medical Center

Abstract Preview: Purpose: Gradient-based optimization is the standard approach for IMRT fluence map optimization (FMO). Recently, a machine learning (ML)-assisted framework using a one-layer neural network was propose...

Real-Time Proton and Carbon Ion Monte Carlo Dose Calculation through GPU-Acceleration and DL-Based Denoising Algorithms

Authors: Yankui Chang, Shijun Li, Xi Pei, Ripeng Wang, Xuanhe Wang, X. George Xu, Qing Zhang, Jingfang Zhao

Affiliation: University of Science and Technology of China, Shanghai proton and heavy ion center, School of Nuclear Science and Technology, University of Science and Technology of China, Anhui Wisdom Technology Co., Ltd.

Abstract Preview: Purpose:
This paper describes disruptive methods using both GPU-based MC simulation and deep-learning (DL)-based MC denoising algorithms, as well as clinical tests involving more than 560 patient p...