Automated worm tracking and classification

The locomotion of C. elegans (a microscopic worm) provides valuable information about mutant genes and their effect on behavior. In order to investigate detailed movement and body posture characteristics of these living animals, advanced automated tracking algorithms are required. Here we describe a novel procedure of tracking an individual worms body part movement accurately by combining head and tail recognition with tracking. In addition, we describe a classification system to distinguish mutant types from each other. We demonstrate that its performance can be improved by incorporating new image features introduced by this tracking method.