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技术说明:放疗应用中部分匹配图像的可变形图像配准。

Technical note: deformable image registration on partially matched images for radiotherapy applications.

机构信息

Department of Radiation Oncology, Washington University, Saint Louis, Missouri 63110, USA.

出版信息

Med Phys. 2010 Jan;37(1):141-5. doi: 10.1118/1.3267547.

Abstract

In radiation therapy applications, deformable image registrations (DIRs) are often carried out between two images that only partially match. Image mismatching could present as superior-inferior coverage differences, field-of-view (FOV) cutoffs, or motion crossing the image boundaries. In this study, the authors propose a method to improve the existing DIR algorithms so that DIR can be carried out in such situations. The basic idea is to extend the image volumes and define the extension voxels (outside the FOV or outside the original image volume) as NaN (not-a-number) values that are transparent to all floating-point computations in the DIR algorithms. Registrations are then carried out with one additional rule that NaN voxels can match any voxels. In this way, the matched sections of the images are registered properly, and the mismatched sections of the images are registered to NaN voxels. This method makes it possible to perform DIR on partially matched images that otherwise are difficult to register. It may also improve DIR accuracy, especially near or in the mismatched image regions.

摘要

在放射治疗应用中,通常在仅部分匹配的两个图像之间进行可变形图像配准(DIR)。图像不匹配可能表现为上/下覆盖差异、视野(FOV)截止或运动越过图像边界。在这项研究中,作者提出了一种改进现有 DIR 算法的方法,以便在这种情况下进行 DIR。基本思想是扩展图像体积并将扩展体素(在 FOV 之外或原始图像体积之外)定义为 NaN(非数字)值,这些值对 DIR 算法中的所有浮点计算都是透明的。然后,通过一个额外的规则进行注册,即 NaN 体素可以匹配任何体素。通过这种方式,图像的匹配部分被正确注册,而图像的不匹配部分被注册到 NaN 体素。该方法使得对否则难以配准的部分匹配图像进行 DIR 成为可能。它还可能提高 DIR 的准确性,尤其是在不匹配的图像区域附近或其中。

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