Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools
Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools
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DOI：
10.3791/61931
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发表时间：
2020-11-01
影响因子：
1.2
通讯作者：
Eliceiri, Kevin W.
中科院分区：
文献类型：
--
作者：
Liu, Yuming;Eliceiri, Kevin W.
纤维状胶原蛋白是重要的细胞外基质 (ECM) 成分，其拓扑结构变化已被证明与多种疾病的进展相关，包括乳腺癌、卵巢癌、肾癌和胰腺癌。免费提供的纤维量化软件工具主要集中于纤维排列或方向的计算，但它们受到诸如需要手动步骤、在噪声背景下检测纤维边缘不准确或缺乏局部特征表征等限制。本协议中描述的胶原纤维定量工具的特点是使用由曲线变换 (CT) 实现的最佳多尺度图像表示。这种算法方法可以去除纤维胶原图像中的噪声并增强纤维边缘，以直接从纤维提供位置和方向信息，而不是使用从其他工具获得的间接像素方式或窗口方式信息。这个基于 CT 的框架包含两个独立但相互关联的软件包，名为“CT-FIRE”和“CurveAlign”，可以在全局、感兴趣区域 (ROI) 或单个纤维的基础上量化纤维组织。这个量化框架已经发展了十多年，现已发展成为一个全面的、用户驱动的胶原蛋白量化平台。使用该平台，人们可以测量多达约三十种纤维特征，包括长度、角度、宽度和直线度等单根纤维特性，以及密度和排列等体积测量。此外，用户可以测量相对于手动或自动分段边界的光纤角度。该平台还提供了几个附加模块，包括用于 ROI 分析、自动边界创建和后处理的模块。使用该平台不需要事先具备编程或图像处理经验，并且可以处理包括数百或数千张图像的大型数据集，从而能够对生物或生物医学应用中的胶原纤维组织进行有效量化。
Fibrillar collagens are prominent extracellular matrix (ECM) components, and their topology changes have been shown to be associated with the progression of a wide range of diseases including breast, ovarian, kidney, and pancreatic cancers. Freely available fiber quantification software tools are mainly focused on the calculation of fiber alignment or orientation, and they are subject to limitations such as the requirement of manual steps, inaccuracy in detection of the fiber edge in noisy background, or lack of localized feature characterization. The collagen fiber quantitation tool described in this protocol is characterized by using an optimal multiscale image representation enabled by curvelet transform (CT). This algorithmic approach allows for the removal of noise from fibrillar collagen images and the enhancement of fiber edges to provide location and orientation information directly from a fiber, rather than using the indirect pixel-wise or window-wise information obtained from other tools. This CT-based framework contains two separate, but linked, packages named "CT-FIRE" and "CurveAlign" that can quantify fiber organization on a global, region of interest (ROI), or individual fiber basis. This quantification framework has been developed for more than ten years and has now evolved into a comprehensive and user-driven collagen quantification platform. Using this platform, one can measure up to about thirty fiber features including individual fiber properties such as length, angle, width, and straightness, as well as bulk measurements such as density and alignment. Additionally, the user can measure fiber angle relative to manually or automatically segmented boundaries. This platform also provides several additional modules including ones for ROI analysis, automatic boundary creation, and post-processing. Using this platform does not require prior experience of programming or image processing, and it can handle large datasets including hundreds or thousands of images, enabling efficient quantification of collagen fiber organization for biological or biomedical applications.