首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.6 no.24 >Identify the Centerline of Tubular Structure in Medical Images
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Identify the Centerline of Tubular Structure in Medical Images

机译:识别医学图像中的管状结构中心线

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Finding the centerline of the tubular structure helps to segment or analyze the organs such as the vessels or neuron fibers in medical images. This paper described a semi-automatic method using the minimum cost path finding and Hessian matrix analysis in scale space to calculate the centerline of tubular structure organs. Unlike previous approaches, exhaustive search for line-like shapes in every scale is prevent. Centerline pixels candidates and the width of the vessel are extracted by analyzing the intensity profile along the gradient vectors in the image. A verification procedure using Hassian matrix analysis with the scale obtained from the gradient analysis is applied to those candidates. Results obtained from the Hessian matrix analysis are used to construct a weighted graph. Finding the minimum cost path in the graph gives the centerline of the tubular structure. The method is applied to find the centerline of the vessels in the 2D angiogram and the neuron fibers in the 3D confocal microscopic images.
机译:查找管状结构的中心线有助于分割或分析医学图像中的器官,例如血管或神经元纤维。本文介绍了一种使用最小成本路径查找和Hessian矩阵分析在尺度空间中计算管状结构器官中心线的半自动方法。与以前的方法不同,可以防止详尽搜索每个比例的线状形状。通过分析沿图像中梯度矢量的强度轮廓来提取候选中心线像素和血管宽度。将使用Hassian矩阵分析和从梯度分析获得的比例的验证过程应用于这些候选对象。从Hessian矩阵分析获得的结果用于构建加权图。在图中找到最小成本路径,即可得出管状结构的中心线。该方法适用于在2D血管造影图中找到血管的中心线,并在3D共焦显微图像中找到神经元纤维。

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