SOAX: A software for quantification of 3D biopolymer networks
نویسندگان
چکیده
Filamentous biopolymer networks in cells and tissues are routinely imaged by confocal microscopy. Image analysis methods enable quantitative study of the properties of these curvilinear networks. However, software tools to quantify the geometry and topology of these often dense 3D networks and to localize network junctions are scarce. To fill this gap, we developed a new software tool called "SOAX", which can accurately extract the centerlines of 3D biopolymer networks and identify network junctions using Stretching Open Active Contours (SOACs). It provides an open-source, user-friendly platform for network centerline extraction, 2D/3D visualization, manual editing and quantitative analysis. We propose a method to quantify the performance of SOAX, which helps determine the optimal extraction parameter values. We quantify several different types of biopolymer networks to demonstrate SOAX's potential to help answer key questions in cell biology and biophysics from a quantitative viewpoint.
منابع مشابه
3D Path Planning Algorithm for Mobile Anchor-Assisted Positioning in Wireless Sensor Networks
Positioning service is one of Wireless Sensor Networks’ (WSNs) fundamental services. The accurate position of the sensor nodes plays a vital role in many applications of WSNs. In this paper, a 3D positioning algorithm is being proposed, using mobile anchor node to assist sensor nodes in order to estimate their positions in a 3D geospatial environment. However, mobile anchor node’s 3D path optim...
متن کاملDeveloping a 3D stochastic discrete fracture network model for hydraulic analyses
Fluid flow in jointed rock mass with impermeable matrix is often controlled by joint properties, including aperture, orientation, spacing, persistence and etc. On the other hand, since the rock mass is made of heterogeneous and anisotropic natural materials, geometric properties of joints may have dispersed values. One of the most powerful methods for simulation of stochastic nature of geometri...
متن کاملHand Gesture Recognition from RGB-D Data using 2D and 3D Convolutional Neural Networks: a comparative study
Despite considerable enhances in recognizing hand gestures from still images, there are still many challenges in the classification of hand gestures in videos. The latter comes with more challenges, including higher computational complexity and arduous task of representing temporal features. Hand movement dynamics, represented by temporal features, have to be extracted by analyzing the total fr...
متن کاملApplication of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data
This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part ofIranwas selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values. Seismic surveying was performed next on these models. F...
متن کاملOptimal Placement and Sizing of DGs and Shunt Capacitor Banks Simultaneously in Distribution Networks using Particle Swarm Optimization Algorithm Based on Adaptive Learning Strategy
Abstract: Optimization of DG and capacitors is a nonlinear objective optimization problem with equal and unequal constraints, and the efficiency of meta-heuristic methods for solving optimization problems has been proven to any degree of complex it. As the population grows and then electricity consumption increases, the need for generation increases, which further reduces voltage, increases los...
متن کامل