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Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.

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第一作者： Florian,Barkmann

第一单位： Institute for Machine Learning, Department of Computer Science, ETH Zürich, Zurich, Switzerland.;Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany.;Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Baden-Württemberg, Germany.

作者： Florian,Barkmann ^[1] ; Yair,Censor ^[2] ; Niklas,Wahl ^[3]

作者单位： Institute for Machine Learning, Department of Computer Science, ETH Zürich, Zurich, Switzerland.;Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany.;Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Baden-Württemberg, Germany. ^[1] Department of Mathematics, Faculty of Natural Sciences, University of Haifa, Haifa, Israel. ^[2] Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany.;Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Baden-Württemberg, Germany. ^[3]

关键词 IMRT constrained treatment plan optimization feasibility-seeking algorithm inverse planning radiation therapy treatment planning superiorization method

DOI 10.3389/fonc.2023.1238824

PMID 38033492

发布时间 2023-12-12

基金项目

R01 CA266467/CA/NCI NIH HHS/United States

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