MOIVRE research center, Sherbrooke, Québec, Canada.
Comput Med Imaging Graph. 2012 Jun;36(4):294-303. doi: 10.1016/j.compmedimag.2011.12.001. Epub 2012 Jan 17.
We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maximum aortic diameter, the volume overlap and the Hausdorff distance) the variability of the results obtained by our method is shown to be similar to that of a human operator, both for the lumen interface and the aortic wall. As will be shown, the average distance obtained with our method is less than one standard deviation away from each expert, both for healthy subjects and for patients with AAA. Our semi-automatic method provides reliable contours of the abdominal aorta from CT-scan or MRI, allowing rapid and reproducible evaluations of AAA.
我们设计了一种通用的方法，用于从多层磁共振成像（MRI）和计算机断层扫描（CT）检查中分割腹主动脉瘤（AAA）的瘤腔。这是一种半自动方法，需要较少的人工干预，并基于图割理论来分割 AAA 的管腔界面和主动脉壁。我们的分割方法独立于 MRI 和 CT 扫描体积，已在 44 名患者数据集和 10 张合成图像上进行了测试。我们将分割和最大直径估计与 4 位专家的手动追踪进行了比较。为了测量人类观察者的可变性范围，进行了一项观察者间研究。基于三个指标（最大主动脉直径、体积重叠和 Hausdorff 距离），我们的方法的结果的可变性与人类操作者的可变性相似，无论是对于管腔界面还是主动脉壁。正如将显示的那样，我们的方法获得的平均距离与每位专家都相差不到一个标准差，无论是对于健康受试者还是对于 AAA 患者都是如此。我们的半自动方法从 CT 扫描或 MRI 提供了可靠的腹主动脉轮廓，允许快速和可重复的 AAA 评估。
