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Deformable image registration in radiation therapy

机译:放射治疗中的可变形图像配准

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摘要

The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use. These applications commonly require a method to align the data sets at a reference. Deformable image registration (DIR) is a process which satisfies this requirement by locally registering image data sets into a reference image set. DIR identifies the spatial correspondence in order to minimize the differences between two or among multiple sets of images. This article describes clinical applications, validation, and algorithms of DIR techniques. Applications of DIR in radiation treatment include dose accumulation, mathematical modeling, automatic segmentation, and functional imaging. Validation methods discussed are based on anatomical landmarks, physical phantoms, digital phantoms, and per application purpose. DIR algorithms are also briefly reviewed with respect to two algorithmic components: similarity index and deformation models.
机译:在将各种先进技术引入放射肿瘤学领域后,放射治疗期间成像数据集的数量已大大增加。结果,已经有许多研究提出了有意义的成像数据集使用的应用。这些应用程序通常需要一种将数据集与参考对齐的方法。可变形图像配准(DIR)是通过将图像数据集本地注册到参考图像集中来满足此要求的过程。 DIR识别空间对应关系,以最小化两组图像之间或多组图像之间的差异。本文介绍了DIR技术的临床应用,验证和算法。 DIR在放射治疗中的应用包括剂量累积,数学建模,自动分割和功能成像。讨论的验证方法基于解剖学界标,物理体模,数字体模以及每个应用目的。还针对两个算法组件简要回顾了DIR算法:相似性索引和变形模型。

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