Celeganser: Automated Analysis of Nematode Morphology and Age
This provides a tool for biologists studying aging and genetics in nematodes, but it is incremental as it builds on existing methods for image analysis.
The authors tackled the problem of automated analysis of C. elegans imagery for aging studies by developing a pipeline that detects, segments, and predicts body coordinates, enabling age prediction with high accuracy.
The nematode Caenorhabditis elegans (C. elegans) serves as an important model organism in a wide variety of biological studies. In this paper we introduce a pipeline for automated analysis of C. elegans imagery for the purpose of studying life-span, health-span and the underlying genetic determinants of aging. Our system detects and segments the worm, and predicts body coordinates at each pixel location inside the worm. These coordinates provide dense correspondence across individual animals to allow for meaningful comparative analysis. We show that a model pre-trained to perform body-coordinate regression extracts rich features that can be used to predict the age of individual worms with high accuracy. This lays the ground for future research in quantifying the relation between organs' physiologic and biochemical state, and individual life/health-span.