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Validation of non-rigid point-set registration methods using a porcine bladder pelvic phantom

机译:验证使用猪膀胱盆腔体模的非刚性定点套准方法

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The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy of utilizing non-rigid (affine or deformable) point-set registration in accumulating dose in bladder of different sizes and shapes. A pelvic phantom was built to house an ex vivo porcine bladder with fiducial landmarks adhered onto its surface. Four different volume fillings of the bladder were used (90, 180, 360 and 480 cc). The performance of MATLAB implementations of five different methods were compared, in aligning the bladder contour point-sets. The approaches evaluated were coherent point drift (CPD), gaussian mixture model, shape context, thin-plate spline robust point matching (TPS-RPM) and finite iterative closest point (ICP-finite). The evaluation metrics included registration runtime, target registration error (TRE), root-mean-square error (RMS) and Hausdorff distance (HD). The reference (source) dataset was alternated through all four points-sets, in order to study the effect of reference volume on the registration outcomes. While all deformable algorithms provided reasonable registration results, CPD provided the best TRE values (6.4 mm), and TPS-RPM yielded the best mean RMS and HD values (1.4 and 6.8 mm, respectively). ICP-finite was the fastest technique and TPS-RPM, the slowest.
机译:在过去的几年中,针对高度可变形器官(如膀胱)的分级放疗中准确剂量累积的问题引起了越来越多的关注。然而,需要更多的研究以找到鲁棒且有效的解决方案并提高当前方法的准确性。这项研究的目的是评估利用非刚性(仿射或可变形)点集套准在不同大小和形状的膀胱中累积剂量的可行性和准确性。建造一个盆腔体模来容纳离体猪膀胱,并在其表面上附着基准标记。使用了四种不同体积的膀胱填充物(90、180、360和480 cc)。在对齐膀胱轮廓点集时,比较了五种不同方法的MATLAB实现的性能。评估的方法是相干点漂移(CPD),高斯混合模型,形状上下文,薄板样条鲁棒点匹配(TPS-RPM)和有限迭代最近点(ICP-finite)。评估指标包括注册运行时间,目标注册错误(TRE),均方根误差(RMS)和Hausdorff距离(HD)。参考(源)数据集通过所有四个点集交替出现,以研究参考量对注册结果的影响。尽管所有可变形算法均提供了合理的配准结果,但CPD提供了最佳的TRE值(6.4毫米),而TPS-RPM产生了最佳的均方根值和HD值(分别为1.4和6.8毫米)。 ICP-limited是最快的技术,而TPS-RPM是最慢的技术。

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