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首页> 外文会议>International Workshop on Computer Vision for Biomedical Image Applications(CVBIA 2005); 20051021; Beijing(CN) >Curvilinear Structure Based Mammographic Registration
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Curvilinear Structure Based Mammographic Registration

机译：基于曲线结构的乳腺X线摄影配准

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摘要

Mammographic registration is a challenging problem due in part to the intrinsic complexity of mammographic images, and partly because of the substantial differences that exist between two mammograms that are to be matched. In this paper, we propose a registration algorithm for mammograms which incorporates junctions of Curvilinear structures (CLS) as internal landmarks. CLS depict connective tissue, blood vessels, and milk ducts. These are detected by an algorithm based on the monogenic signal and afforced by a CLS physical model. The junctions are extracted using a local energy (LE)-based method, which utilises the orientation information provided by the monogenic signal. Results using such junctions as internal landmarks in registration are presented and compared with conventional approaches using boundary landmarks, in order to highlight the potential of anatomical based feature extraction in medical image analysis. We demonstrate how computer vision techniques such as phase congruency (PC), local energy (LE) and multi-resolution can be applied in linear (1-D) and junction (2-D) detection as well as their application to medical image registration problems.
机译：乳腺摄影配准是一个具有挑战性的问题，部分原因是乳腺摄影图像的固有复杂性，部分原因是要匹配的两个乳腺摄影之间存在实质性差异。在本文中，我们提出了一种针对乳房X线照片的配准算法，该算法结合了曲线结构（CLS）的结点作为内部界标。 CLS描绘结缔组织，血管和乳腺导管。通过基于单基因信号的算法检测到这些，并在CLS物理模型的支持下进行检测。使用基于局部能量（LE）的方法提取连接点，该方法利用了单基因信号提供的方向信息。提出了使用这种结作为配准中的内部界标的结果，并与使用边界界标的常规方法进行了比较，以突出医学图像分析中基于解剖特征的特征提取的潜力。我们演示了如何将诸如相位一致性（PC），局部能量（LE）和多分辨率的计算机视觉技术应用于线性（1-D）和交界处（2-D）检测以及它们在医学图像配准中的应用问题。

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