Intensity-based 2-D-3-D registration of cerebral angiograms
Intensity-based 2-D-3-D registration of cerebral angiograms
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DOI：
10.1109/tmi.2003.819283
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发表时间：
2003-11-01
影响因子：
10.6
通讯作者：
Hawkes, DJ
中科院分区：
文献类型：
--
作者：
Hipwell, JH;Penney, GP;Hawkes, DJ
提出了一种新的三维磁共振血管造影（MRA）与二维X射线数字减影血管造影（I）的配准方法。我们的方法是从我们的算法，注册计算机断层扫描体积的X射线图像的基础上强度匹配的数字重建的射线照片（DRR）。为了使DSA和DRR更相似，我们将MRA图像转换为血管图像，并将MRA的对侧设置为零，以DSA成像。我们初始化搜索用户定义的圆形感兴趣区域的匹配。我们已经测试了六个相似性措施，使用未分割的MRA和三个分割变体的MRA。对物理神经血管体模的图像和在四次神经血管介入期间获得的图像进行配准。当与最复杂的MRA分割结合使用时，使用模式强度、梯度差和梯度相关相似性度量获得最准确和最稳健的配准。使用这些措施，95%的体模开始位置和82%的临床开始位置被成功配准。体模和临床数据集的最低均方根重投影误差分别为1.3 mm（标准差0.6）和1.5 mm（标准差0.9）。最后，我们提出了一种新的方法，使用从接收机运营商的特征分析借用的技术的相似性度量性能的比较。
We propose a new method for aligning three-dimensional (3-D) magnetic resonance angiography (MRA) with 2-D X-ray digital subtraction angiograms (I)SA). Our method is developed from our algorithm to register computed tomography volumes to X-ray images based on intensity matching of digitally reconstructed radiographs (DRRs). To make the DSA and DRR more similar, we transform the MRA images to images of the vasculature and set to zero the contralateral side of the MRA to that imaged with DSA. We initialize the search for a match on a user defined circular region of interest. We have tested six similarity measures using both unsegmented MRA and three segmentation variants of the MRA. Registrations were carried out on images of a physical neuro-vascular phantom and images obtained during four neuro-vascular interventions. The most accurate and robust registrations were obtained using the pattern intensity, gradient difference, and gradient correlation similarity measures, when used in conjunction with the most sophisticated MRA segmentations. Using these measures, 95% of the phantom start positions and 82% of the clinical start positions were successfully registered. The lowest root mean square reprojection errors were 1.3 mm (standard deviation 0.6) for the phantom and 1.5 mm (standard deviation 0.9) for the clinical data sets. Finally, we present a novel method for the comparison of similarity measure performance using a technique borrowed from receiver operator characteristic analysis.