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A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models

机译:基于多尺度滤波和统计模型的多模态血管造影图像血管分割方法

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摘要

BackgroundAccurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images.
机译:背景技术血管的精确分割在血管疾病的计算机辅助诊断和介入治疗中起着重要作用。统计方法是有效分割血管的重要组成部分。然而,一些限制阻碍了分割效果,即,依赖于图像模态,不均匀的造影剂,偏置场以及对象和背景的重叠强度分布。另外,根据图像直方图的特征构建统计方法的混合模型。因此,对于从多模态血管造影图像中进行血管分割而言,传统方法是一个具有挑战性的问题。

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