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Demons Deformable Registration for Cone-Beam CT Guidance: Registration of Pre- and Intra-Operative Images

机译:锥束CT引导的恶魔可变形配准:术前和术中图像的配准

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High-quality intraoperative 3D imaging systems such as cone-beam CT (CBCT) hold considerable promise for image-guided surgical procedures in the head and neck. With a large amount of preoperative imaging and planning information available in addition to the intraoperative images, it becomes desirable to be able to integrate all sources of imaging information within the same anatomical frame of reference using deformable image registration. Fast intensity-based algorithms are available which can perform deformable image registration within a period of time short enough for intraoperative use. However, CBCT images often contain voxel intensity inaccuracy which can hinder registration accuracy - for example, due to x-ray scatter, truncation, and/or erroneous scaling normalization within the 3D reconstruction algorithm. In this work, we present a method of integrating an iterative intensity matching step within the operation of a multi-scale Demons registration algorithm. Registration accuracy was evaluated in a cadaver model and showed that a conventional Demons implementation (with either no intensity match or a single histogram match) introduced anatomical distortion and degradation in target registration error (TRE). The iterative intensity matching procedure, on the other hand, provided robust registration across a broad range of intensity inaccuracies.
机译:诸如锥梁CT(CBCT)的高质量术中的3D成像系统对头部和颈部的图像引导的手术程序保持相当大的承诺。除了术中图像之外可用的大量术前成像和规划信息,还希望能够使用可变形图像配准在相同的解剖学框架内集成所有成像信息源。可提供基于快速的基于强度的算法,其可以在足够短的时间内执行可变形的图像配准以进行术中使用。然而,CBCT图像通常包含体素强度不准确,这可以阻碍注册精度 - 例如,由于3D重建算法内的X射线散射,截断和/或错误的缩放标准化。在这项工作中,我们介绍了一种在多尺度恶魔登记算法的操作中集成迭代强度匹配步骤的方法。在Cadaver模型中评估了登记精度,并显示了传统的恶魔实现(具有不强匹配或单个直方图匹配)引入了目标登记误差(TRE)中的解剖学失真和降级。另一方面,迭代强度匹配程序在广泛的强度不准确方面提供了强大的注册。

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