Xu Ting, Vavylonis Dimitrios, Huang Xiaolei
Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA.
Department of Physics, Lehigh University, Bethlehem, PA, USA.
Med Image Anal. 2014 Feb;18(2):272-84. doi: 10.1016/j.media.2013.10.015. Epub 2013 Nov 16.
Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels.
荧光显微镜常用于研究由细胞骨架聚合物纤维（如肌动蛋白丝和肌动蛋白束）形成的二维和三维网络结构。虽然这些细胞骨架结构通常足够稀疏，能够对单个细丝或细丝束进行成像，但对这些图像进行定量分析具有挑战性。为了便于对图像数据进行定量、可重复和客观的分析，我们提出了一种半自动方法，用于提取肌动蛋白网络并检索其三维拓扑结构。我们的方法使用多个拉伸开放活动轮廓（SOAC），这些轮廓在图像强度脊处自动初始化，然后沿着网络中细丝的中心线演化。SOAC可以合并，在交叉点处停止，并与其他轮廓重新配置，以便在细丝交叉点处平滑交叉。所提出的方法通常适用于低信噪比的曲线网络图像。我们通过提取合成网格图像的中心线、二维全内反射荧光显微镜图像中的肌动蛋白网络以及旋转盘共聚焦显微镜成像的活裂殖酵母细胞的三维肌动蛋白束网络，展示了其潜力。使用合成图像对该方法进行定量评估表明，对于信噪比高于5.0的图像，通过我们的结果与真实值之间的距离测量的平均顶点误差为1体素，平均豪斯多夫距离低于10体素。
