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从CT图像中提取支气管分支的自动命名法及其在虚拟支气管镜检查活检路径规划中的应用。

Automated nomenclature of bronchial branches extracted from CT images and its application to biopsy path planning in virtual bronchoscopy.

作者信息

Mori Kensaku, Ema Sinya, Kitasaka Takayuki, Mekada Yoshito, Ide Ichiro, Murase Hiroshi, Suenaga Yasuhito, Takabatake Hirotsugu, Mori Masaki, Natori Hiroshi

机构信息

Grad. School of Information Science, Nagoya University, Nagoya 464-8603, Japan.

出版信息

Med Image Comput Comput Assist Interv. 2005;8(Pt 2):854-61. doi: 10.1007/11566489_105.

Abstract

We propose a novel anatomical labeling algorithm for bronchial branches extracted from CT images. This method utilizes multiple branching models for anatomical labeling. In the actual labeling process, the method selects the best candidate models at each branching point. Also a special labeling procedure is proposed for the right upper lobe. As an application of the automated nomenclature of bronchial branches, we utilized anatomical labeling results for assisting biopsy planning. When a user inputs a target point around suspicious regions on the display of a virtual bronchoscopy (VB) system, the path to the desired position is displayed as a sequence of anatomical names of branches. We applied the proposed method to 25 cases of CT images. The labeling accuracy was about 90%. Also the paths to desired positions were generated by using anatomical names in VB.

摘要

我们提出了一种用于从CT图像中提取支气管分支的新型解剖学标记算法。该方法利用多种分支模型进行解剖学标记。在实际标记过程中,该方法在每个分支点选择最佳候选模型。此外,还针对右上叶提出了一种特殊的标记程序。作为支气管分支自动命名法的一种应用,我们利用解剖学标记结果辅助活检计划。当用户在虚拟支气管镜(VB)系统的显示屏上输入可疑区域周围的目标点时,通往所需位置的路径会显示为分支的解剖学名称序列。我们将所提出的方法应用于25例CT图像。标记准确率约为90%。此外,还通过在VB中使用解剖学名称生成了通往所需位置的路径。

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