• Corpus ID: 204743742

Deep learning for accelerating Monte Carlo radiation transport simulation in intensity-modulated radiation therapy

@article{Peng2019DeepLF,
  title={Deep learning for accelerating Monte Carlo radiation transport simulation in intensity-modulated radiation therapy},
  author={Zhao Peng and Hongming Shan and Tianyu Liu and Xi Pei and Jieping Zhou and Ge Wang and X. George Xu},
  journal={arXiv: Medical Physics},
  year={2019}
}
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 distribution maps in patient need to be calculated and evaluated for the purpose of killing tumor and protecting healthy tissue. Monte Carlo (MC) radiation transport calculation is able to account for all aspects of radiological physics within 3D heterogeneous media such as the human body and generate the dose distribution maps… 

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