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Volume Registration of Interventional MRI Data Using Needle Paths and Point Landmarks

机译:使用针路径和点标志性的介入MRI数据的音量登记

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We created a method for three-dimensional registration of medical scanner image volumes to images of physical tissue sections or other volumes, and evaluated its accuracy. The method is applicable for many animal experiments, and we are applying it to evaluate interventional MRI imaging of thermal ablation and to quantify in vivo drug release from a new device for localized, controlled release. The method computes an optimum set of rigid body registration parameters by iterative minimization of the Euclidean distances between automatically generated correspondence points, along manually selected fiducial needle paths, and optional point landmarks. For numerically simulated registrations, using two needle paths over a range of needle orientations, median voxel displacement errors depended only on needle localization error when the angle between needles was at least 15 degrees. For parameters typical of our in vivo experiments, the median error was ≤ 0.18 mm. In addition, we determined that the distance objective function was a useful diagnostic for predicting registration quality. To evaluate the registration quality of physical specimens, we computed the misregistration for a needle not considered during the optimization procedure. We registered an ex vivo sheep brain MR volume with another MR volume and tissue section photographs, using various combinations of needle and point landmarks. Registration error was always ≤ 0.65 mm for MR-to-MR registrations and ≤ 0.9 mm for MR to tissue section registrations. We conclude that our method provides sufficient spatial correspondence to facilitate comparison of 3D image data with data from gross pathology tissue sections and histology.
机译:我们创建了一种方法,用于医疗扫描仪图像卷的三维登记,对物理组织部分或其他体积的图像,并评估其精度。该方法适用于许多动物实验,并申请它来评估热消融的介入MRI成像,并从用于局部,控释的新装置中的体内药物释放量化。该方法通过迭代最小化自动生成的对应点之间的欧几里德距离的迭代最小化,沿着手动选择的基准针路径和可选点地标的迭代最小化的最佳刚体注册参数集。对于数值模拟的注册,在一系列针取向范围内使用两个针路径,当针之间的角度至少为15度时,中位体素位移误差仅取决于针定位误差。对于我们在体内实验的典型参数,中值误差≤0.18毫米。此外,我们确定距离目标函数是预测登记质量的有用诊断。为了评估物理标本的注册质量,我们计算了在优化程序期间未考虑的针头的误解。我们使用针对针头和点标志性的各种组合,使用另一种MR卷和组织部分照片注册了前体内绵羊脑MR卷。对于MR-MR注册,注册误差始终≤0.65mm,对于组织部分注册,≤0.9mm。我们得出结论,我们的方法提供了足够的空间对应,以便于将3D图像数据与来自总理病理组织部分和组织学的数据进行比较。

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