Automated worm tracking and classification

Author

Geng, Wei ; Cosman, Pamela ; Huang, Clare ; Schafer, William R.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., La Jolla, CA, USA

Volume

2

fYear

2003

fDate

9-12 Nov. 2003

Firstpage

2063

Abstract

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.

Keywords

biological techniques; biology computing; genetics; image classification; image motion analysis; tracking; zoology; C. elegans locomotion; advanced automated worm tracking algorithm; automated worm classification; body part movement; body posture characteristic; head recognition; image feature; living animal; mutant gene; mutant type; tail recognition; Animals; Computer worms; Head; Microorganisms; Microscopy; Nervous system; Neurons; Soil; Tail; Tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on

Print_ISBN

0-7803-8104-1

Type

conf

DOI

10.1109/ACSSC.2003.1292343

Filename

1292343