Institute for Applied Computer Science (IACS), University of Applied Sciences, Zur Schwedenschanze 15, D-18435 Stralsund, Germany.
Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Strasse 3, D-72076 Tübingen, Germany.
Comput Med Imaging Graph. 2018 Dec;70:29-42. doi: 10.1016/j.compmedimag.2018.09.005. Epub 2018 Sep 25.
Recently, in diffusion magnetic resonance imaging, the reconstruction and three-dimensional rendering of white matter pathways have been introduced to clinical routine protocols. In a number of clinical situations, for example the preoperative analysis of vascular pathologies, the assessment of spatial relations between vascular structures and nearby fiber pathways is of vital interest for treatment planning. In this paper, we present an approach to the integrated vessel and fiber visualization, based on a novel vascular contrast enhancement operator for Magnetic Resonance Angiography (MRA) datasets. We propose a 3D dynamic programming method, allowing contrast enhancement of vascular structures and suppression of partial voluming effects at vessel borders. This makes it easier to visualize vascular structures by realtime volume rendering with surface shading. In contrast to maximum intensity projection, the method provides better depth cues and allows for easier spatial orientation. The integration of tractography-generated fibers as streamlines or streamtubes with correct visibility computation is performed by a combined volume and geometry renderer. In situations where tractography fails to provide reliable results, we use a line integral convolution method to assess white matter structures. In this manner, the spatial relations of vessels to fiber structures can be depicted by three-dimensional visualizations. We evaluate our approach with clinical data from patients with arteriovenous malformations, stenoses, aneurysms, and from healthy volunteers.
最近，在弥散磁共振成像中，已经将白质通路的重建和三维渲染引入临床常规方案中。在许多临床情况下，例如血管病变的术前分析，评估血管结构与附近纤维通路之间的空间关系对于治疗计划至关重要。在本文中，我们提出了一种基于新型磁共振血管造影（MRA）数据集血管对比增强算子的血管和纤维综合可视化方法。我们提出了一种 3D 动态规划方法，允许增强血管结构并抑制血管边界的部分容积效应。这使得通过实时体绘制和表面阴影更容易可视化血管结构。与最大强度投影相比，该方法提供了更好的深度提示，并允许更容易的空间定位。通过组合体积和几何渲染器，将轨迹生成的纤维作为流线或流管与正确的可见性计算进行集成。在轨迹无法提供可靠结果的情况下，我们使用线积分卷积方法来评估白质结构。通过这种方式，可以通过三维可视化描绘血管与纤维结构的空间关系。我们使用来自动静脉畸形、狭窄、动脉瘤患者和健康志愿者的临床数据评估我们的方法。
