A pseudoinverse deformation vector field generator and its applications.
A pseudoinverse deformation vector field generator and its applications.
复制标题
一种伪逆变形矢量场发生器及其应用。
DOI：
10.1118/1.3301594
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发表时间：
2010
期刊：
影响因子：
3.8
通讯作者：
Siebers,JV
中科院分区：
文献类型：
--
作者：
Yan,C;Zhong,H;Murphy,M;Weiss,E;Siebers,JV
PurposeTo提出，实现和测试自一致的伪逆位移向量场（PIDVF）生成器，它保留了图像sets.MethodsThe算法之间来回映射的信息的位置是一个迭代方案的基础上最近邻插值和随后的迭代搜索。使用肺部4DCT数据集对算法的性能进行基准测试，该数据集具有来自不同呼吸阶段的六幅CT图像和在不同日期采集的单个前列腺患者的八幅CT图像。一个同构变形图像配准被用来验证我们的PIDVF。此外，PIDVF用于测量两种不使用自一致性约束的非同构算法的自一致性：用于肺部患者图像的ITK Demons算法和用于前列腺患者图像的内部B‐Spline算法。Demons和B‐Spline都通过轮廓比较进行了QA。自一致性是通过使用一个插值器在参考图像和研究图像之间生成位移矢量场（DVF）来确定的。使用相同的函数来生成。此外，我们的PIDVF生成器用于创建。将使用和对一组点（用作轮廓替代项）进行的来回映射与使用和执行的来回映射进行比较。原始未映射点和映射点之间的欧氏距离被用作自我一致性measure.ResultsTest结果表明，在来回映射中观察到的一致性误差可以减少2至9倍，在点映射和剂量映射时，使用PIDVF代替B-样条算法的1.5至3倍。这些自我一致性的改进不受交换和的影响。它也表明，之间的差异和可以被用来作为一个标准，以检查质量的DVF.ConclusionsUse的DVF和它的PIDVF将提高自我一致性的点，轮廓，和剂量映射在图像引导的自适应治疗。
PurposeTo present, implement, and test aself‐consistent pseudoinverse displacement vector field(PIDVF) generator, which preserves the location of information mapped back‐and‐forth between image sets.MethodsThe algorithm is an iterative scheme based on nearest neighbor interpolation and a subsequent iterative search. Performance of the algorithm is benchmarked using a lung 4DCT data set with six CT images from different breathing phases and eight CT images for a single prostrate patient acquired on different days. A diffeomorphic deformable image registration is used to validate our PIDVFs. Additionally, the PIDVF is used to measure the self‐consistency of two nondiffeomorphic algorithms which do not use a self‐consistency constraint: The ITK Demons algorithm for the lung patient images and an in‐house B‐Spline algorithm for the prostate patient images. Both Demons and B‐Spline have been QAed through contour comparison. Self‐consistency is determined by using a DIR to generate a displacement vector field (DVF) between reference image and study image . The same DIR is used to generate . Additionally, our PIDVF generator is used to create . Back‐and‐forth mapping of a set of points (used as surrogates of contours) using and is compared to back‐and‐forth mapping performed with and . The Euclidean distances between the original unmapped points and the mapped points are used as a self‐consistency measure.ResultsTest results demonstrate that the consistency error observed in back‐and‐forth mappings can be reduced two to nine times in point mapping and 1.5 to three times in dose mapping when the PIDVF is used in place of the B‐Spline algorithm. These self‐consistency improvements are not affected by the exchanging of and . It is also demonstrated that differences between and can be used as a criteria to check the quality of the DVF.ConclusionsUse of DVF and its PIDVF will improve the self‐consistency of points, contour, and dose mappings in image guided adaptive therapy.