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自适应放疗中用于非刚性配准算法的三维定量评估方法。

Three-dimensional quantitative evaluation method of nonrigid registration algorithms for adaptive radiotherapy.

机构信息

Bioengineering and Telemedicine Group, Technical University of Madrid, Madrid 28040, Spain.

出版信息

Med Phys. 2010 Mar;37(3):1137-45. doi: 10.1118/1.3302916.

Abstract

PURPOSE

Current radiotherapy is progressing to the concept of adaptive radiotherapy, which implies the adaptation of planning along the treatment course. Nonrigid registration is an essential image processing tool for adaptive radiotherapy and image guided radiotherapy, and the three-dimensional (3D) nature of the current radiotherapy techniques requires a 3D quantification of the registration error that existing evaluation methods do not cover appropriately. The authors present a method for 3D evaluation of nonrigid registration algorithms' performance, based on organ delineations, capable of working with near-spherical volumes even in the presence of concavities.

METHODS

The evaluation method is composed by a volume shape description stage, developed using a new ad hoc volume reconstruction algorithm proposed by the authors, and an error quantification stage. The evaluation method is applied to the organ delineations of prostate and seminal vesicles, obtained by an automatic segmentation method over images of prostate cancer patients treated with intensity modulated radiation therapy.

RESULTS

The volume reconstruction algorithm proposed has been shown to accurately model complex 3D surfaces by the definition of clusters of control points. The quantification method, inspired by the Haussdorf-Chebysev distance, provides a measure of the largest registration error per control direction, defining a valid metric for concave-convex volumes. Summarizing, the proposed evaluation methodology presents accurate results with a high spatial resolution in a negligible computation time in comparison with the nonrigid registration time.

CONCLUSIONS

Experimental results show that the metric selected for quantifying the registration error is of utmost importance in a quantitative evaluation based on measuring distances between volumes. The accuracy of the volume reconstruction algorithm is not so relevant as long as the reconstruction is tight enough on the actual volume of the organ. The new evaluation method provides a smooth and accurate volume reconstruction for both the reference and the registered organ, and a complete 3D description of nonrigid registration algorithms' performance, resulting in a useful tool for study and comparison of registration algorithms for adaptive radiotherapy.

摘要

目的

目前的放射治疗正在向自适应放射治疗的概念发展,这意味着需要沿着治疗过程来调整计划。非刚性配准是自适应放射治疗和图像引导放射治疗的基本图像处理工具,而当前放射治疗技术的三维(3D)性质需要对现有评估方法无法适当涵盖的配准误差进行 3D 量化。作者提出了一种基于器官勾画的非刚性配准算法性能的 3D 评估方法,该方法能够在存在凹陷的情况下处理近球形体积。

方法

该评估方法由一个体积形状描述阶段和一个误差量化阶段组成。体积形状描述阶段使用作者提出的一种新的专门体积重建算法进行开发。评估方法应用于前列腺和精囊的器官勾画,这些勾画是通过对接受调强放射治疗的前列腺癌患者的图像进行自动分割获得的。

结果

所提出的体积重建算法通过定义控制点簇,准确地对复杂的 3D 表面进行建模。基于 Haussdorf-Chebysev 距离的量化方法提供了一种测量每个控制方向上最大配准误差的方法,为凹凸体积定义了有效的度量标准。总之,与非刚性配准时间相比,所提出的评估方法在计算时间上具有较高的空间分辨率,能够提供准确的结果。

结论

实验结果表明,在基于测量体积之间距离的定量评估中,用于量化配准误差的度量标准非常重要。只要重建足够紧密地贴合器官的实际体积,体积重建算法的准确性就不是那么重要。新的评估方法为参考器官和注册器官提供了平滑和准确的体积重建,以及非刚性配准算法性能的完整 3D 描述,为自适应放射治疗的配准算法研究和比较提供了有用的工具。

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