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首页> 外文会议>Visualization, Image-Guided Procedures pt.2; Progress in Biomedical Optics and Imaging; vol.8 no.28; Proceedings of SPIE-The International Society for Optical Engineering; vol.6509 pt.2 >Stochastic Rank Correlation for slice-to-volume registration of FluoroCT/CT imaging
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Stochastic Rank Correlation for slice-to-volume registration of FluoroCT/CT imaging

机译：用于FluoroCT / CT成像的切片到体积配准的随机秩相关

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摘要

Slice-to-Volume registration is a special case of 2D/3D registration where a single slice obtained using a stationary-scanner geometry is registered to a pre-interventional diagnostic volume scan. Examples include interventional magnetic resonance imaging (IMRI) or fluoroscopic computed tomography (CT). In a recent study in Fluo-roCT/CT registration, we have shown that conventional cross correlation (CC), together with repeated use of conventional local optimization algorithms, provides an optimum measure for slice-to-volume registration for mo-noenergetic CT imaging data. If the required linear relationship between corresponding pixel pairs is offended (e. g. by using X-rays of different energy or by varying detector characteristics), CC becomes an unreliable measure of image similarity. A more general merit function like normalized mutual information (NMI) serves better in such a case but is stricken with local minima caused by sparse population of joint histograms. We present a novel merit function for 2D/3D registration named stochastic rank correlation (SRC), which is well-suited for in-tramodal dual-energy imaging. A first evaluation of SRC is given on a set of simulated and clinical FluoroCT/CT scan image data sets.
机译：切片到体积的配准是2D / 3D配准的一种特殊情况，其中将使用固定式扫描仪几何体获得的单个切片配准到介入前诊断体积扫描。示例包括介入磁共振成像（IMRI）或荧光透视X线断层扫描（CT）。在Fluo-roCT / CT配准的最新研究中，我们显示了常规互相关（CC），以及重复使用常规局部优化算法，为单能CT成像的切片到体积配准提供了最佳方法数据。如果违反了相应像素对之间所需的线性关系（例如，通过使用不同能量的X射线或通过改变检测器特性），则CC成为图像相似性的不可靠度量。在这种情况下，诸如归一化互信息（NMI）之类的更一般的优点函数会更好，但会因联合直方图稀疏而引起局部最小值。我们提出了一种名为随机等级相关性（SRC）的2D / 3D注册新功能，它非常适合于模态内双能成像。在一组模拟和临床FluoroCT / CT扫描图像数据集上对SRC进行了首次评估。

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