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Fiber finding algorithm using stepwise tracing to identify biopolymer fibers in noisy 3D images
Biophysical Journal ( IF 3.2 ) Pub Date : 2021-08-17 , DOI: 10.1016/j.bpj.2021.08.017
Ninna Struck Rossen 1 , Anders Kyrsting 2 , Amato J Giaccia 3 , Janine Terra Erler 4 , Lene Broeng Oddershede 2
Affiliation  

We present a novel fiber finding algorithm (FFA) that will permit researchers to detect and return traces of individual biopolymers. Determining the biophysical properties and structural cues of biopolymers can permit researchers to assess the progression and severity of disease. Confocal microscopy images are a useful method for observing biopolymer structures in three dimensions, but their utility for identifying individual biopolymers is impaired by noise inherent in the acquisition process, including convolution from the point spread function (PSF). The new, iterative FFA we present here 1) measures a microscope’s PSF and uses it as a metric for identifying fibers against the background; 2) traces each fiber within a cone angle; and 3) blots out the identified trace before identifying another fiber. Blotting out the identified traces in each iteration allows the FFA to detect and return traces of single fibers accurately and efficiently—even within fiber bundles. We used the FFA to trace unlabeled collagen type I fibers—a biopolymer used to mimic the extracellular matrix in in vitro cancer assays—imaged by confocal reflectance microscopy in three dimensions, enabling quantification of fiber contour length, persistence length, and three-dimensional (3D) mesh size. Based on 3D confocal reflectance microscopy images and the PSF, we traced and measured the fibers to confirm that colder gelation temperatures increased fiber contour length, persistence length, and 3D mesh size—thereby demonstrating the FFA’s use in quantifying biopolymers’ structural and physical cues from noisy microscope images.



中文翻译:

使用逐步追踪来识别嘈杂 3D 图像中的生物聚合物纤维的纤维查找算法

我们提出了一种新的纤维发现算法 (FFA),它将允许研究人员检测并返回单个生物聚合物的痕迹。确定生物聚合物的生物物理特性和结构线索可以让研究人员评估疾病的进展和严重程度。共聚焦显微镜图像是观察三维生物聚合物结构的有用方法,但它们在识别单个生物聚合物方面的效用受到采集过程中固有的噪声的影响,包括来自点扩散函数 (PSF) 的卷积。我们在此介绍的新的迭代 FFA 1) 测量显微镜的 PSF 并将其用作识别背景纤维的指标;2) 在锥角内跟踪每根光纤;3) 在识别另一根光纤之前涂抹已识别的痕迹。在每次迭代中抹去已识别的痕迹使 FFA 能够准确有效地检测和返回单根光纤的痕迹——即使在光纤束内也是如此。我们使用 FFA 追踪未标记的 I 型胶原纤维——一种用于在体外癌症检测中模拟细胞外基质的生物聚合物——通过共聚焦反射显微镜在三个维度上成像,从而能够量化纤维轮廓长度、持久长度和三维。 3D) 网格尺寸。基于 3D 共焦反射显微镜图像和 PSF,我们追踪并测量了纤维,以确认较冷的凝胶温度增加了纤维轮廓长度、持久长度和 3D 网格尺寸,从而证明了 FFA 在量化生物聚合物的结构和物理线索方面的用途嘈杂的显微镜图像。

更新日期:2021-09-21
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