Intensity-modulated radiation therapy (IMRT) was developed in order to deliver a highly conformal dose to tumor while bearing surrounding normal tissue, especially critical organs, under clinically acceptable dose level. For achieving this goal, multiple beams with modulated fluence maps from different angles were required. This raised the issue of how to optimally select the beams to best meet the clinical goal of radiotherapy. This book provided an intelligence guided approach based on fuzzy inference system to automate beam angle optimization in treatment planning of IMRT. A fuzzy inference system was established in simulating the reasoning process of human planners while they were working on treatment planning of IMRT. Two spinal cases were investigated in this study and the preliminary results show that dose quality of IMRT plans achieved by this approach is superior to those achieved by the default approach with equally spaced beam setting. It discovered the potential of fuzzy inference system on IMRT optimization, and especially useful for those who may consider utilizing automated software tool in beam angle optimization of treatment planning of IMRT.
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Born in 1973, China. 1997-2001 PhD, Dept. of Automation, Tsinghua University, China. 2001-2003 PostDoc, Dept. of Radiation Oncology, Henry Ford Hospital, USA. 2004-2014 Assistant Prof., Dept. of Radiation Oncology, Duke University, USA. 2015-Current Assoc. Prof. Dept. of Radiation Oncology, Cancer Hospital Chinese Academy of Medical Science, China.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Intensity-modulated radiation therapy (IMRT) was developed in order to deliver a highly conformal dose to tumor while bearing surrounding normal tissue, especially critical organs, under clinically acceptable dose level. For achieving this goal, multiple beams with modulated fluence maps from different angles were required. This raised the issue of how to optimally select the beams to best meet the clinical goal of radiotherapy. This book provided an intelligence guided approach based on fuzzy inference system to automate beam angle optimization in treatment planning of IMRT. A fuzzy inference system was established in simulating the reasoning process of human planners while they were working on treatment planning of IMRT. Two spinal cases were investigated in this study and the preliminary results show that dose quality of IMRT plans achieved by this approach is superior to those achieved by the default approach with equally spaced beam setting. It discovered the potential of fuzzy inference system on IMRT optimization, and especially useful for those who may consider utilizing automated software tool in beam angle optimization of treatment planning of IMRT. 52 pp. Englisch. Seller Inventory # 9783330024373
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yan HuiBorn in 1973, China. 1997-2001 PhD, Dept. of Automation, Tsinghua University, China. 2001-2003 PostDoc, Dept. of Radiation Oncology, Henry Ford Hospital, USA. 2004-2014 Assistant Prof., Dept. of Radiation Oncology, Duke Univer. Seller Inventory # 158247010
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Intensity-modulated radiation therapy (IMRT) was developed in order to deliver a highly conformal dose to tumor while bearing surrounding normal tissue, especially critical organs, under clinically acceptable dose level. For achieving this goal, multiple beams with modulated fluence maps from different angles were required. This raised the issue of how to optimally select the beams to best meet the clinical goal of radiotherapy. This book provided an intelligence guided approach based on fuzzy inference system to automate beam angle optimization in treatment planning of IMRT. A fuzzy inference system was established in simulating the reasoning process of human planners while they were working on treatment planning of IMRT. Two spinal cases were investigated in this study and the preliminary results show that dose quality of IMRT plans achieved by this approach is superior to those achieved by the default approach with equally spaced beam setting. It discovered the potential of fuzzy inference system on IMRT optimization, and especially useful for those who may consider utilizing automated software tool in beam angle optimization of treatment planning of IMRT.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Seller Inventory # 9783330024373
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Intensity-modulated radiation therapy (IMRT) was developed in order to deliver a highly conformal dose to tumor while bearing surrounding normal tissue, especially critical organs, under clinically acceptable dose level. For achieving this goal, multiple beams with modulated fluence maps from different angles were required. This raised the issue of how to optimally select the beams to best meet the clinical goal of radiotherapy. This book provided an intelligence guided approach based on fuzzy inference system to automate beam angle optimization in treatment planning of IMRT. A fuzzy inference system was established in simulating the reasoning process of human planners while they were working on treatment planning of IMRT. Two spinal cases were investigated in this study and the preliminary results show that dose quality of IMRT plans achieved by this approach is superior to those achieved by the default approach with equally spaced beam setting. It discovered the potential of fuzzy inference system on IMRT optimization, and especially useful for those who may consider utilizing automated software tool in beam angle optimization of treatment planning of IMRT. Seller Inventory # 9783330024373
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Taschenbuch. Condition: Neu. Intelligence Guidence in Beam Optimization of Radiotherapy | Fuzzy Inference System based Beam Optimization in Treatment Planning of Radiation Therapy | Hui Yan | Taschenbuch | 52 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330024373 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 108263128