Extraction and analysis of actin networks based on Open Active Contour models

Abstract

Network structures formed by actin filaments are present in many kinds of fluorescence microscopy images. In order to quantify the conformations and dynamics of such actin filaments, we propose a fully automated method to extract actin networks from images and analyze network topology. The method handles well intersecting filaments and, to some extent, overlapping filaments. First we automatically initialize a large number of Stretching Open Active Contours (SOACs) from ridge points detected by searching for plus-to-minus sign changes in the gradient map of the image. These initial SOACs then elongate simultaneously along the bright center-lines of filaments by minimizing an energy function. During their evolution, they may merge or stop growing, thus forming a network that represents the topology of the filament ensemble. We further detect junction points in the network and break the SOACs at junctions to obtain "SOAC segments". These segments are then re-grouped using a graph-cut spectral clustering method to represent the configuration of actin filaments. The proposed approach is generally applicable to extracting intersecting curvilinear structures in noisy images. We demonstrate its potential using two kinds of data: (1) actin filaments imaged by Total Internal Reflection Fluorescence Microscopy (TIRFM) in vitro; (2) actin cytoskeleton networks in fission yeast imaged by spinning disk confocal microscopy.

3D actin network centerline extraction with multiple active contours

“…Unlike previous methods that relied on a global intensity contrast (Li et al, 2009a; Smith et al, 2010; Xu et al, 2011), Equation 7 generates stretching force that is adaptable according to local intensity contrast around SOAC tips. This can avoid under-segmentation for dim filaments in low-intensity backgrounds or over-segmentation for bright filaments in high-intensity backgrounds.…”

“…In a previous study (Xu et al, 2011), we have shown how multiple Stretching Open Active Contours (SOACs) that elongate and merge with one another can be used to segment networks of actin filaments in 2D TIRFM images, such as in Figure 1(a). In this article we present an extension and significant modification of the multiple SOACs method to address the more complex issues that arise in 3D and to propose mechanisms that make the approach robust to heavy image noise, non-uniform filament and background intensity, and anisotropic sampling as are typical in many 3D experimental images.…”

“…We propose novel mechanisms that eliminate any redundancies by allowing the SOACs to merge, stop at junctions, and transform into closed curve forms. In Xu et al (2011) all of the initial SOACs evolved simultaneously. Here we found that sequential evolution according to a specific set of rules (a process we refer to as “regulated sequential evolution”) is a more robust method.…”

A Systems-Biology Approach to Yeast Actin Cables

“…Reported automated two-dimensional methods that distill stacks of images into filament locations and network topologies [29] (Fig. 3D) could be extended to three dimensions.…”

“…A fit to a double exponential (continuous line) leads to length scales l 1 = 2 μ m and l 2 = 1 mm [28]. (D) Automatic segmentation of 2D filament network using multiple active contours from [29]. A meshwork is generated by initialization of multiple active contours at ridge points followed by growth, merging and splitting of active contours.…”