Automated Tracking of Multiple C. Elegans

Abstract

This paper presents a method for model based automated tracking of multiple worm-like creatures. These methods are essential for accurate quantitative analysis into the genetic basis of behavior that involve more than one organism. An accurate worm model is designed using the geometry of planar curves and nonlinear estimation of the model's parameters are performed using a central difference Kalman filter (CDKF). The filter can naturally be expanded to estimate the locations of multiple worms and determine when they are occluding each other. The predicted location of the models at each iteration allows for an efficient method to determine the regions that are undergoing occlusions. Experiments on actual C. Elegans mating sequence data demonstrate the quality of the proposed method.

Robust tracking and quantification ofC. elegansbody shape and locomotion through coiling, entanglement, and omega bends

“…This approach furthers our previous work 33, 34 and incorporates formalisms from Fontaine et al 35,36 to create a framework for the automated Figure 1. Illustrative images of C. elegans on nematode growth medium (NGM) plates in challenging tracking scenarios: (A) interaction between 2 worms, (B) coiling with self occlusion of the worm contour, (C) high amplitude bending.…”

“…[33][34][35][36] In a previous publication, Roussel et al defined crawling as a combination of peristaltic progression and radial displacement. In this paper, crawling is modeled as peristaltic progression and change of the angle model parameters.…”

“…[33][34][35][36] The parameter u is normalized over the range [ ¡ 0:5; 0:5] such that M 0 ð Þ is the midpoint position of the detected worm shape, M ¡ 0:5 ð Þits tail, and M 0:5 ð Þ its head. The bending angle Q u ð Þ along the centerline is similarly defined and modeled using a third order periodic B-spline basis ff 3 j g composed of a default number of N Q D 8 splines (1).…”

Automated visual tracking for studying the ontogeny of zebrafish swimming

“…Creating deformable models based on medial profiles has been used in segmentation problems in medical imaging (Hamarneh and McInerney, 2001) and for tracking multiple C. elegans from 0 0.2 0.4 microscopy images (Fontaine et al, 2006;Roussel et al, 2007). Because zebrafish are laterally symmetric about their body axis, our medial profile representation offers several advantages for the tracking framework.…”

“…The body shape can therefore be described effectively by the bend angle Θ of the fish as a function of distance along its length, u. This function, Θ(u), is finitely parameterized using a linear combination of known basis functions where Φ k j (u), is the jth basis function of order k. The current implementation uses eight (N Θ =8) periodic cubic B-splines as the basis functions, which we found to be sufficient to capture the different bending modes of the swimming zebrafish and mating Caenorhabditis elegans (Fontaine et al, 2006). Other choices in the order and number of basis functions are possible.…”