Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
IEEE Trans Biomed Eng. 2012 Apr;59(4):996-1004. doi: 10.1109/TBME.2011.2182051. Epub 2011 Dec 28.
Virtual colonoscopy detects polyps by navigating along a colon centerline. Complete colon segmentation based on computed tomography (CT) data is a prerequisite to the computation of complete colon centerline. There are two main problems impeding complete segmentation: overdistention/underdistention of colon and the use of oral contrast agents. Overdistention produces loops in the segmented colon, while underdistention may cause the segmented colon collapse into a series of disconnected segments. Use of oral contrast agents, which have high attenuation on CT, may add redundant structures (bones and small bowels) to the segmented colon. A fully automated colon segmentation method is proposed in this paper to address the two problems. We tested the proposed method in 170 cases, including 37 "moderate" and 133 "challenging" cases. Computer-generated centerlines were compared with human-generated centerlines (plotted by three radiologists). The proposed method achieved a 90.56% correct coverage rate with respect to the human-generated centerlines. We also compared the proposed method with two existing colon segmentation methods: Uitert's method and Nappi's method. The results of these two methods were 75.16% and 72.59% correct coverage rates, respectively. Our experimental results indicate that the proposed method could yield more complete colon centerlines than the existing methods.
虚拟结肠镜检查通过沿结肠中心线导航来检测息肉。基于计算机断层扫描 (CT) 数据的完整结肠分割是计算完整结肠中心线的前提。有两个主要问题阻碍了完整的分割：结肠过度膨胀/欠膨胀和口服对比剂的使用。过度膨胀会导致分割的结肠出现环，而欠膨胀可能会导致分割的结肠塌陷成一系列不连续的段。在 CT 上具有高衰减的口服对比剂可能会向分割的结肠添加多余的结构（骨骼和小肠）。本文提出了一种全自动的结肠分割方法来解决这两个问题。我们在 170 个病例中测试了该方法，包括 37 个“中度”和 133 个“挑战性”病例。计算机生成的中心线与人工生成的中心线（由三位放射科医生绘制）进行了比较。该方法在覆盖人工生成的中心线方面的准确率达到了 90.56%。我们还将该方法与现有的两种结肠分割方法（Uitert 方法和 Nappi 方法）进行了比较。这两种方法的结果分别为 75.16%和 72.59%的准确率。我们的实验结果表明，该方法可以比现有的方法生成更完整的结肠中心线。
