Deformable Registration Method Using Edge Preserving Scale Space withApplication in Adaptive Radiation Therapy
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摘要: 计划CT图像与锥形束CT (Cone beam CT, CBCT)图像的配准是基于CBCT图像引导放射治疗(Image guided radiation therapy, IGRT)系统中实现自适应放疗(Adaptive radiation therapy, ART)的关键部分.边缘保护多尺度空间基于非线性扩散模型,可以为基于互信息的配准提供丰富的空间位置信息.为了提高系统中配准算法性能,本文提出了一种基于边缘保护尺度空间与自由形变模型(Free form deformation, FFD)相结合的多尺度形变配准方法.我们采用了在不同的尺度上根据精细程度选择相应的自由形变控制点数,由粗及精地恢复形变.同时, 提出了自动获取非线性扩散模型中平滑参数λ的方法来实现全自动配准. 实验结果表明,本文提出的方法用于基于CBCT的图像引导放射系统时,可实现日常放疗时的CBCT图像和计划CT图像准确且快速的配准.通过获得的形变域,可实现CBCT图像肿瘤靶区、危及器官(Organ at risk, OR)和等剂量线的自动勾画,从而实现剂量体积直方图(Dose volume histograms, DVH)分析.最终实现了放疗计划从CT到CBCT的自适应转移.Abstract: Registration of planning CT with daily cone beam CT (CBCT) images is an important component for adaptive radiation therapy in CBCT based image guided radiation therapy (IGRT) system. The edge preserving scale space which is derived from the anisotropic diffusion model can provide abundant spatial information for mutual information based registration. For improving the registration efficiency in system, a multi-scale deformable registration framework is proposed by combining edge preserving scale space with the multi-level free form deformation (FFD) grids. Different scales use different FFD grid, where the deformation fields are gained by a coarse to fine manner. Furthermore, considering clinical application, we design an optimal method for estimation of the parameters in anisotropic diffusion model for automated registration. The experiment results demonstrate that the proposed method can register the daily CBCT with the planning CT accurately and has a promising efficiency when used in CBCT based IGRT system. After gaining the deformation field, tumor target, organ at risk (OR) and iso-dose are contoured automatically, and then ''DVH (Dose volume histograms) analysis'' are also studied. Finally, radiation planning is transferred from planning CT to daily CBCT images adaptively.
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