| 期刊全稱 | 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy | | 影響因子2023 | Jan Ehrhardt,Cristian Lorenz | | 視頻video | http://file.papertrans.cn/101/100888/100888.mp4 | | 發(fā)行地址 | Deals with the hot topic of pulmonary motion for medical imaging, image processing and therapeutic applications.Gives a cutting edge overview on the topic, written by very notable authors in the field | | 學(xué)科分類 | Biological and Medical Physics, Biomedical Engineering | | 圖書封面 |  | | 影響因子 | Respiratory motion causes an important uncertainty in radiotherapy planning of the thorax and upper abdomen. The main objective of radiation therapy is to eradicate or shrink tumor cells without damaging the surrounding tissue by delivering a high radiation dose to the tumor region and a dose as low as possible to healthy organ tissues. Meeting this demand remains a challenge especially in case of lung tumors due to breathing-induced tumor and organ motion where motion amplitudes can measure up to several centimeters. Therefore, modeling of respiratory motion has become increasingly important in radiation therapy. With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient’s body. Furthermore, image registration enables the estimation of the breathing-induced motion and the description of the temporal change in position and shape of the structures of interest by establishing the correspondence between images acquired at different phases of the breathing cycle. In radiation therapy these motion estimations are used to define accurate treatment margins, e.g. to calculate dose distributions and to develop prediction models | | Pindex | Book 2013 |
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