三维 MDCT 图像中中央胸部淋巴结的分割。
Segmentation of the central-chest lymph nodes in 3D MDCT images.
机构信息
Department of Electrical Engineering, Penn State University, University Park, PA 16802, USA.
出版信息
Comput Biol Med. 2011 Sep;41(9):780-9. doi: 10.1016/j.compbiomed.2011.06.014. Epub 2011 Jul 12.
Abstract
Central-chest lymph nodes play a vital role in lung-cancer staging. The definition of lymph nodes from three-dimensional (3D) multidetector computed-tomography (MDCT) images, however, remains an open problem. We propose two methods for computer-based segmentation of the central-chest lymph nodes from a 3D MDCT scan: the single-section live wire and the single-click live wire. For the single-section live wire, the user first applies the standard live wire to a single two-dimensional (2D) section after which automated analysis completes the segmentation process. The single-click live wire is similar but is almost completely automatic. Ground-truth studies involving human 3D MDCT scans demonstrate the robustness, efficiency, and intra-observer and inter-observer reproducibility of the methods.
摘要
纵隔淋巴结在肺癌分期中起着至关重要的作用。然而，从三维（3D）多排螺旋 CT（MDCT）图像中定义淋巴结仍然是一个悬而未决的问题。我们提出了两种基于计算机的方法，用于从 3D MDCT 扫描中分割纵隔淋巴结：单节实时线和单点击实时线。对于单节实时线，用户首先将标准实时线应用于单个二维（2D）截面，然后自动分析完成分割过程。单点击实时线与之类似，但几乎完全是自动的。涉及人体 3D MDCT 扫描的真实研究证明了这些方法的稳健性、效率以及观察者内和观察者间的可重复性。
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