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A 3D Model of Human Cerebrovasculature Derived from 3T Magnetic Resonance Angiography

机译:来自3T磁共振血管造影的人类脑血管系统3D模型

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The human cerebrovasculature is extremely complicated and its three dimensional (3D) highly parcellated models, though necessary, are unavailable. We constructed a digital cerebrovascular model from a high resolution, 3T 3D time-of-flight magnetic resonance angiography scan. This model contains the arterial and venous systems and is 3D, geometric, highly parcellated, fully segmented, and completely labeled with name, diameter, and variants. Our approach replaces the tedious and time consuming process of checking and correcting automatic segmentation results done at 2D image level with an aggregate and faster process at 3D model level. The creation of the vascular model required vessel pre-segmentation, centerline extraction, vascular segments connection, centerline smoothing, vessel surface construction, vessel grouping, tracking, editing, labeling, setting diameter, and checking correctness and completeness. For comparison, the same scan was segmented automatically with 59.8% sensitivity and only 16.5% of vessels smaller than 1 pixel size were extracted. To check and correct this automatic segmentation requires 8 weeks. Conversely, the speedup of our approach (the number of 2D segmented areas/the number of 3D vascular segments) is 34. This cerebrovascular model can serve as a reference framework in clinical, research, and educational applications. The wealth of information aggregated with its quantification capabilities can augment or replace numerous textbook chapters. Five applications of the vascular model were described. The model is easily extendable in content, parcellation, and labeling, and the proposed approach is applicable for building a whole body vascular system.
机译:人类的脑血管系统极其复杂,尽管有必要,但其三维(3D)高分离模型却不可用。我们从高分辨率的3T 3D飞行时间磁共振血管造影扫描中构建了数字化脑血管模型。该模型包含动脉和静脉系统,并且是3D,几何,高度分散的,完全分段的,并带有名称,直径和变体的完全标记。我们的方法用3D模型级的聚合更快的过程代替了检查和纠正在2D图像级完成的自动分割结果的繁琐且耗时的过程。血管模型的创建需要进行血管预分割,中心线提取,血管段连接,中心线平滑,血管表面构造,血管分组,跟踪,编辑,标记,设置直径以及检查正确性和完整性。为了进行比较,同一扫描以59.8%的灵敏度自动进行了分割,并且仅提取了小于像素大小1的血管的16.5%。要检查并纠正此自动细分,需要8周的时间。相反,我们的方法的加速速度(2D分割区域的数量/ 3D血管段的数量)为34。这种脑血管模型可以作为临床,研究和教育应用的参考框架。丰富的信息及其量化功能可以扩充或替代许多教科书章节。描述了血管模型的五种应用。该模型可以轻松地扩展内容,分类和标签,并且所提出的方法适用于构建全身血管系统。

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