Detecting Attached Worm Eggs using Deformable Template Matching

W. Geng, P. Cosman, and W.R. Schafer (USA)

Keywords

machine learning, computer vision, c. elegans, egglaying.

Abstract

Egg-laying is an important phase of the life cycle of the nematode Caenorhabditis elegans (C. elegans). Previous studies examined egg-laying events manually. This paper presents a method for automatic detection of egg-laying onset using deformable template matching and other morphological image analysis techniques. Some behavioral changes surrounding egg-laying events are also studied. The results demonstrate that the computer vision tools and algorithm developed here can be effectively used to study C. elegans egg-laying behaviors. The algorithm developed will be an essential part of a machine vision system for C. elegans tracking and behavioral analysis.

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