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用于自适应放射治疗的计划CT与每日锥形束CT图像的多尺度配准

Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy.

作者信息

Paquin Dana, Levy Doron, Xing Lei

机构信息

Department of Mathematics, California Polytechnic State University, San Luis Obispo, California 93407, USA.

出版信息

Med Phys. 2009 Jan;36(1):4-11. doi: 10.1118/1.3026602.

Abstract

Adaptive radiation therapy (ART) is the incorporation of daily images in the radiotherapy treatment process so that the treatment plan can be evaluated and modified to maximize the amount of radiation dose to the tumor while minimizing the amount of radiation delivered to healthy tissue. Registration of planning images with daily images is thus an important component of ART. In this article, the authors report their research on multiscale registration of planning computed tomography (CT) images with daily cone beam CT (CBCT) images. The multiscale algorithm is based on the hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [Multiscale Model. Simul. 2(4), pp. 554-579 (2004)]. Registration is achieved by decomposing the images to be registered into a series of scales using the (BV, L2) decomposition and initially registering the coarsest scales of the image using a landmark-based registration algorithm. The resulting transformation is then used as a starting point to deformably register the next coarse scales with one another. This procedure is iterated at each stage using the transformation computed by the previous scale registration as the starting point for the current registration. The authors present the results of studies of rectum, head-neck, and prostate CT-CBCT registration, and validate their registration method quantitatively using synthetic results in which the exact transformations our known, and qualitatively using clinical deformations in which the exact results are not known.

摘要

自适应放射治疗(ART)是在放射治疗过程中纳入每日图像,以便评估和修改治疗计划,从而在使输送到健康组织的辐射量最小化的同时,使给予肿瘤的辐射剂量最大化。因此,计划图像与每日图像的配准是ART的一个重要组成部分。在本文中,作者报告了他们关于计划计算机断层扫描(CT)图像与每日锥束CT(CBCT)图像的多尺度配准的研究。该多尺度算法基于E. Tadmor、S. Nezzar和L. Vese的分层多尺度图像分解方法[《多尺度模型与模拟》2(4),第554 - 579页(2004年)]。通过使用(BV,L2)分解将待配准图像分解为一系列尺度,并首先使用基于地标点的配准算法配准图像最粗糙的尺度来实现配准。然后,将得到的变换用作起点,以相互变形配准下一个较粗糙的尺度。在每个阶段都迭代此过程,将前一尺度配准计算得到的变换用作当前配准的起点。作者展示了直肠、头颈部和前列腺CT - CBCT配准的研究结果,并使用已知精确变换的合成结果进行定量验证,以及使用未知精确结果的临床变形进行定性验证。

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