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共聚焦激光扫描显微镜下角蛋白中间丝的三维分割

3D segmentation of keratin intermediate filaments in confocal laser scanning microscopy.

作者信息

Herberich Gerlind, Windoffer Reinhard, Leube Rudolf, Aach Til

机构信息

Institute of Imaging & Computer Vision, RWTH Aachen University, 52056 Aachen, Germany.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:7751-4. doi: 10.1109/IEMBS.2011.6091910.

Abstract

In this paper, we propose and compare different methods for the 3D segmentation of keratin intermediate filaments (KFs) in images acquired using confocal laser scanning microscopy (CLSM). KFs are elastic cables forming a complex scaffolding within epithelial cells. They are involved in many basic cell functions. To understand the mechanisms of filament formation and network organisation under physiological and pathological conditions, quantitative measurements of dynamic network alterations are essential. Segmenting KFs is a key component for analyzing their dynamic and biomechanical properties. KFs were labeled with fluorescent keratins to allow high resolution imaging of network dynamics in native cells. Our segmentation methods follow the principle of ridge enhancement filtering and subsequent centerline extraction. The evaluation of the methods is two-fold: (i) We develop synthetic data that exhibit the characteristics of real CLSM data to evaluate the precision of the different methods in terms of centerline localisation and (ii) we perform a connected component analysis on the segmentation results of real KF data to assess whether the connectivity of highly complex networks is being preserved by the segmentation. Our evaluation shows that in the presence of strong noise and despite the highly anisotropic spatial resolution of CLSM images the proposed method is able to accurately localize the centerlines of the KFs and to preserve the KF networks' connectivity. Taken together this is a strong indicator that also the network topology is being preserved.

摘要

在本文中,我们提出并比较了多种用于在共聚焦激光扫描显微镜(CLSM)采集的图像中对角蛋白中间丝(KF)进行三维分割的方法。KF是在上皮细胞内形成复杂支架结构的弹性索。它们参与许多基本的细胞功能。为了理解在生理和病理条件下丝形成和网络组织的机制,对动态网络变化进行定量测量至关重要。分割KF是分析其动态和生物力学特性的关键部分。通过用荧光角蛋白标记KF,以便对天然细胞中的网络动态进行高分辨率成像。我们的分割方法遵循脊增强滤波和后续中心线提取的原则。对这些方法的评估有两个方面:(i)我们生成具有真实CLSM数据特征的合成数据,以评估不同方法在中心线定位方面的精度;(ii)我们对真实KF数据的分割结果进行连通分量分析,以评估高度复杂网络的连通性是否通过分割得以保留。我们的评估表明,在存在强噪声且尽管CLSM图像具有高度各向异性的空间分辨率情况下,所提出的方法能够准确地定位KF的中心线并保留KF网络的连通性。综合来看,这有力地表明网络拓扑结构也得以保留。

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