Lazebnik Roee S, Lancaster Tanya L, Breen Michael S, Lewin Jonathan S, Wilson David L
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106-7207 USA.
IEEE Trans Med Imaging. 2003 May;22(5):653-60. doi: 10.1109/TMI.2003.812246.
We created a method for three-dimensional (3-D) registration of medical images (e.g., magnetic resonance imaging (MRI) or computed tomography) to images of physical tissue sections or to other medical images and evaluated its accuracy. Our method proved valuable for evaluation of animal model experiments on interventional-MRI guided thermal ablation and on a new localized drug delivery system. The method computes an optimum set of rigid body registration parameters by minimization of the Euclidean distances between automatically chosen correspondence points, along manually selected fiducial needle paths, and optional point landmarks, using the iterative closest point algorithm. For numerically simulated experiments, using two needle paths over a range of needle orientations, mean voxel displacement errors depended mostly on needle localization error when the angle between needles was at least 20 degrees. For parameters typical of our in vivo experiments, the mean voxel displacement error was < 0.35 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. Mean registration error was always < or = 0.54 mm for MR-to-MR registrations and < or = 0.52 mm for MR to tissue section registrations. We also applied the method to correlate MR volumes of radio-frequency induced thermal ablation lesions with actual tissue destruction. In this case, in vivo rabbit thigh volumes were registered to photographs of ex vivo tissue sections using two needle paths. Mean registration errors were between 0.7 and 1.36 mm over all rabbits, the largest error less than two MR voxel widths. We conclude that our method provides sufficient spatial correspondence to facilitate comparison of 3-D image data with data from gross pathology tissue sections and histology.
我们创建了一种用于将医学图像（如磁共振成像（MRI）或计算机断层扫描）与物理组织切片图像或其他医学图像进行三维（3-D）配准的方法，并评估了其准确性。我们的方法被证明对于评估介入MRI引导下热消融和新型局部药物递送系统的动物模型实验很有价值。该方法通过使用迭代最近点算法，沿着手动选择的基准针路径以及可选的点标记，最小化自动选择的对应点之间的欧几里得距离，来计算一组最佳的刚体配准参数。对于数值模拟实验，在一系列针方向上使用两条针路径，当针之间的角度至少为20度时，平均体素位移误差主要取决于针的定位误差。对于我们体内实验的典型参数，平均体素位移误差<0.35毫米。此外，我们确定距离目标函数是预测配准质量的有用诊断指标。为了评估物理标本的配准质量，我们计算了优化过程中未考虑的针的配准误差。我们使用针和点标记的各种组合，将离体绵羊脑MR体积与另一个MR体积和组织切片照片进行配准。对于MR到MR配准，平均配准误差始终<或=0.54毫米，对于MR到组织切片配准，平均配准误差<或=0.52毫米。我们还应用该方法将射频诱导热消融病变的MR体积与实际组织破坏情况相关联。在这种情况下，使用两条针路径将体内兔大腿体积与离体组织切片照片进行配准。所有兔子的平均配准误差在0.7至1.36毫米之间，最大误差小于两个MR体素宽度。我们得出结论，我们的方法提供了足够的空间对应关系，便于将3-D图像数据与大体病理组织切片和组织学数据进行比较。
