Applications of machine learning to improve the clinical viability of compton camera based in vivo range veri fi cation in proton radiotherapy

HIGHLIGHTS

  • who: Jerimy C. Polf et al. from the Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, United States, Department of have published the Article: Applications of Machine Learning to Improve the Clinical Viability of Compton Camera Based in vivo Range Veri fi cation in Proton Radiotherapy, in the Journal: (JOURNAL)
  • what: The authors report on the use of a more complex deep, fully connected NN for expanded types of preprocessing of PG data measured with a CC during delivery of a clinical proton RT beam to a tissue equivalent target. The . . .

     

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