Subasić Marko, Loncarić Sven, Sorantin Erich
Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia.
Comput Methods Programs Biomed. 2005 Nov;80(2):103-14. doi: 10.1016/j.cmpb.2005.06.009. Epub 2005 Aug 22.
Abdominal aortic aneurysm (AAA) is a serious vascular disease which may have a fatal outcome. AAA shape and size is important for diagnostics and intervention planning. In this paper, we present a new method for segmentation of AAA from computed tomography (CT) angiography images. The method works by segmenting the inner and the outer aortic border. Segmentation of AAA is a challenging problem because of low contrast of the outer aortic border. In our method, the inner aortic border is segmented using a geometric deformable model (GDM) and morphological postprocessing. The GDM is implemented using the level-set algorithm. The outer aortic border is segmented by a preprocessing method utilizing a priori knowledge about the aorta shape, followed by the GDM-based method, and morphological postprocessing. The preprocessing algorithm operates on a slice-by-slice basis with some information flow among neighboring slices. The GDM performs three-dimensional (3D) segmentation, reducing possible errors in the previous step. The proposed method is automatic and requires minimal user assistance. The method was statistically validated on 12 patient scans having a total number of 497 image slices. Statistical analysis has confirmed high correlation between the results obtained by the proposed method and the gold standard obtained by manual segmentation by an expert radiologist.
腹主动脉瘤（AAA）是一种严重的血管疾病，可能会导致致命后果。AAA的形状和大小对于诊断和干预计划很重要。在本文中，我们提出了一种从计算机断层扫描（CT）血管造影图像中分割AAA的新方法。该方法通过分割主动脉的内边界和外边界来工作。由于主动脉外边界的对比度较低，AAA的分割是一个具有挑战性的问题。在我们的方法中，使用几何可变形模型（GDM）和形态学后处理来分割主动脉内边界。GDM使用水平集算法实现。主动脉外边界通过利用关于主动脉形状的先验知识的预处理方法进行分割，随后是基于GDM的方法和形态学后处理。预处理算法逐片操作，相邻切片之间有一些信息流。GDM执行三维（3D）分割，减少上一步中可能出现的错误。所提出的方法是自动的，并且需要最少的用户协助。该方法在12例患者扫描上进行了统计验证，共有497个图像切片。统计分析证实了所提出的方法获得的结果与专家放射科医生手动分割获得的金标准之间具有高度相关性。
