多对比度三维MRI数据中颅内血管准确血管壁可视化的稳健中心线预测
Robust Centerline Prediction for Accurate Vessel Wall Visualization of Intracranial Vessels in Multi-Contrast 3D MRI Data
摘要：
颅内动脉的准确平面可视化（曲面重建- CPR）对于改善管腔和壁评估是强制性的，特别是在标准临床环境中采集的低分辨率磁共振成像（MRI）数据集中。基于所需结构的中心线的CPR可视化方法快速且易于实现，但准确性强烈依赖于3D数据集的空间分辨率和所需血管的大小。在手稿中，提出了一种新的算法，快速和强大的中心线计算在多对比度的三维MRI数据。它考虑了血管结构的提取表面，以获得更准确的中心线预测，从而增强小血管的CPR可视化。
英文摘要：
An accurate planar visualization (curved planar reformation - CPR) of intracranial arteries is mandatory for an improved luminal and mural assessment especially in low resolution Magnetic Resonance Imaging (MRI) data sets acquired in standard clinical settings. CPR visualization methods based on the centerline of the desired structure are fast and easy to implement but the accuracy strongly depends on the spatial resolution of the 3D data set and the size of the desired vessel. In the manuscript, a novel algorithm for fast and robust centerline calculation in multi-contrast 3D MRI data is presented. It considers the extracted surface of the vessel structure for a more accurate centerline prediction resulting in an enhanced CPR visualization of small vessels.
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