首页> 外文会议>Physiology, Function, and Structure from Medical Images pt.1; Progress in Biomedical Optics and Imaging; vol.7,no.29 >Branch identification method for CT-guided bronchoscopy based on eigenspace image matching between real and virtual bronchoscopic images
【24h】

Branch identification method for CT-guided bronchoscopy based on eigenspace image matching between real and virtual bronchoscopic images

机译:基于真实与虚拟支气管镜图像特征空间图像匹配的CT引导支气管镜分支识别方法

获取原文
获取原文并翻译 | 示例

摘要

This paper presents a method for identifying branches for CT-guided bronchoscopy based on eigenspace image matching. This method outputs the current location of a real bronchoscope (RB) by displaying branches where a bronchoscope is currently observing or by presenting anatomical names of branches currently being observed. In the previous method of bronchoscope navigation, the motion of a real bronchoscope is tracked by image registration between RB and virtual bronchoscopic (VB) images. Although bronchoscope tracking based on image registration gives us very accurate tracking results, it requires a lot of computation time and it is difficult to perform real-time tracking. If we focus only on navigation to a target branch, it is enough to identify a branch where a bronchoscope is currently located. This paper presents a method for identifying branches in which a bronchoscope is currently observing and presenting their anatomical names. Branch identification is done by image matching between RB images and pre-generated VB images. VB images are pre-generated at each bifurcation point based on structural analysis results of bronchi regions extracted from CT images. For each frame of an RB video, we find the most similar VB image to the input one from a training dataset (pre-generated VB image) and output the branch levels associated with the found image by using the eigenspace method. We have applied the proposed method to a pair of comprising a 3D CT image and real bronchoscopic video. The experimental results showed that the proposed method can identify branches for about 77.7% of the input frames.
机译:本文提出了一种基于特征空间图像匹配的CT引导支气管镜分支识别方法。此方法通过显示支气管镜当前正在观察的分支或通过显示当前正在观察的分支的解剖学名称来输出实际支气管镜(RB)的当前位置。在支气管镜导航的先前方法中,通过在RB和虚拟支气管镜(VB)图像之间进行图像配准来跟踪实际支气管镜的运动。尽管基于图像配准的支气管镜跟踪可以为我们提供非常准确的跟踪结果,但它需要大量的计算时间,并且很难执行实时跟踪。如果我们仅关注导航到目标分支,则足以识别支气管镜当前所在的分支。本文提出了一种用于识别支气管镜当前正在观察的分支的方法,并提供其解剖名称。分支识别是通过RB图像和预生成的VB图像之间的图像匹配完成的。根据从CT图像中提取的支气管区域的结构分析结果,在每个分叉点处预先生成VB图像。对于RB视频的每一帧,我们从训练数据集中找到与输入图像最相似的VB图像(预生成的VB图像),并使用特征空间方法输出与找到的图像相关的分支级别。我们已将所提出的方法应用于包括3D CT图像和实际支气管镜视频的一对。实验结果表明,该方法可以识别约77.7%的输入帧的分支。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号