Institute of Biomedical Engineering, National Yang-Ming University, 155 Linong Street, Section 2, Beitou, Taipei 112, Taiwan.
Med Phys. 2009 Dec;36(12):5612-21. doi: 10.1118/1.3260841.
Three-dimensional rotational angiography (3DRA) is an evolving imaging procedure from traditional digital subtraction angiography and is gaining much interest for detecting intracranial aneurysms. Computational fluid dynamics (CFD) modeling plays an important role in understanding the biomechanical properties and in facilitating the prediction of aneurysm rupture. A successful computational study relies on an accurate description of the vascular geometry that is obtained from volumetric images.
The authors propose a new aneurysm segmentation algorithm to facilitate the study of CFD. This software combines a region-growing segmentation method with the 3D extension of a deformable contour based on a charged fluid model. A charged fluid model essentially consists of a set of charged elements that are governed by the nature of electrostatics. The approach requires no prior knowledge of anatomic structures and automatically segments the vasculature after the end-user selects a vessel section in a plane image.
Experimental results on 15 cases indicate that aneurysm structures were effectively segmented and in good agreement with manual delineation outcomes. In comparison with the existing methods, the algorithm provided a much higher overlap index with respect to the ground truth. Furthermore, the outcomes of the proposed approach achieved a clean representation of vascular structures that is advantageous for hemodynamics analyses.
A new aneurysm segmentation framework in an attempt to automatically segment vascular structures in 3DRA image volumes has been developed. The proposed algorithm demonstrated promising performance and unique characteristics to adequately segment aneurysms in 3DRA image volumes for further study in computational fluid dynamics.
三维旋转血管造影（3DRA）是从传统数字减影血管造影发展而来的一种成像技术，对于检测颅内动脉瘤具有很大的兴趣。计算流体动力学（CFD）建模在理解生物力学特性和促进动脉瘤破裂预测方面发挥着重要作用。成功的计算研究依赖于从体积图像中获得的血管几何形状的准确描述。
作者提出了一种新的动脉瘤分割算法，以方便 CFD 的研究。该软件结合了基于电荷流模型的可变形轮廓的 3D 扩展的区域生长分割方法。电荷流模型本质上由一组受静电性质支配的带电元素组成。该方法不需要先验的解剖结构知识，并且在用户在平面图像中选择血管截面后，自动对血管进行分割。
15 例实验结果表明，动脉瘤结构得到了有效分割，与手动勾画结果吻合良好。与现有的方法相比，该算法与真实值的重叠指数更高。此外，该方法的结果提供了血管结构的清晰表示，有利于血液动力学分析。
提出了一种新的动脉瘤分割框架，试图自动分割 3DRA 图像体积中的血管结构。所提出的算法表现出了有前景的性能和独特的特点，能够充分分割 3DRA 图像体积中的动脉瘤，以进一步进行计算流体动力学研究。
