Machine learning based oxygen and carbon concentration derivation using dual‐energy CT for PET‐based dose verification in proton therapy

PURPOSE: Online dose verification based on proton-induced positron emitters requires high accuracy in the assignment of elemental composition (e.g., C and O). We developed a machine learning framework for deriving oxygen and carbon concentration based on dual-energy CT (DECT). METHODS: Digital phantoms at the head site were constructed based on single-energy CT (SECT) and stoichiometric calibration. DECT images (80 and 140 kVp) were synthesized …