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微血管网络的计算机辅助定量分析:应用于仓鼠病理性血管生成引起的改变。

Computer-aided quantification of microvascular networks: Application to alterations due to pathological angiogenesis in the hamster.

作者信息

Bulant Carlos A, Blanco Pablo J, Müller Lucas O, Scharfstein Julio, Svensjö Erik

机构信息

Laboratório Nacional de Computação Científica, LNCC/MCTI, Av. Getúlio Vargas 333, Quitandinha, 25651-075 Petrópolis, Brazil.

Instituto de Biofísica Carlos Chagas Filho, UFRJ, Rio de Janeiro, Brazil.

出版信息

Microvasc Res. 2017 Jul;112:53-64. doi: 10.1016/j.mvr.2017.03.004. Epub 2017 Mar 12.

Abstract

Angiogenesis is both a physiological and a pathological process of great complexity, which is difficult to measure objectively and automatically. The hamster cheek pouch (HCP) prepared for intravital-microscopy (IVM) has been used to characterize microvascular functions in many studies and was chosen to investigate microvascular characteristics observed in normal non-infected hamsters as compared to those HCPs parasitized by Trypanosoma cruzi. Images of HCPs captured at IVM were subjected to computer based measurements of angiogenesis and histamine-induced macromolecular (FITC-dextran) leakage with an image segmentation approach that has the capacity to discriminate between fluorescence emitted by macromolecular tracers inside the vasculature and in the extravascular space. We present such an automatic segmentation methodology using known tools from image processing field that, to our knowledge, have not been tested in IVM images. We have compared this methodology with a recently published segmentation strategy based on image intensity thresholding. Our method renders an accurate and robust segmentation of blood vessels for different microvascular scenarios, normal and pathological. Application of the proposed strategy for objective and automatic measurement of angiogenesis detection was explored in detail.

摘要

血管生成是一个极其复杂的生理和病理过程,难以进行客观和自动的测量。为活体显微镜检查(IVM)制备的仓鼠颊囊(HCP)已在许多研究中用于表征微血管功能,并被选来研究正常未感染仓鼠的微血管特征,与被克氏锥虫寄生的HCP的微血管特征进行比较。在IVM下捕获的HCP图像采用一种图像分割方法进行基于计算机的血管生成测量以及组胺诱导的大分子(异硫氰酸荧光素标记的葡聚糖)渗漏测量,该方法能够区分血管内和血管外空间中大分子示踪剂发出的荧光。我们展示了一种使用图像处理领域已知工具的自动分割方法,据我们所知,这些工具尚未在IVM图像中进行测试。我们已将此方法与最近发表的基于图像强度阈值化的分割策略进行了比较。我们的方法针对不同的微血管情况,包括正常和病理情况,都能对血管进行准确且稳健的分割。详细探讨了所提出的策略在血管生成检测的客观和自动测量中的应用。

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