Name
Title | ||
|---|---|---|
A Micropositioning System with Real-Time Feature Extraction Capability for Quantifying C. elegans Locomotive Behavior |
Abstract | ||
|---|---|---|
Tracking C. elegans and extracting locomotive features of the nematode allow the investigation of how genes control behavioral phenotypes. Existing systems require large storage space for image data recording and significant time for off-line processing. This paper presents a visually servoed micropositioning system capable of extracting locomotive features on line at a full 30 Hz. The employment of Gaussian pyramid Level-2 images significantly reduces the image size by 16 folds and permits real-time feature extraction, without sacrificing accuracy due to the cubic smoothing spline fitting. Enabled by the capability of the micropositioning system in revealing subtle differences in locomotive behavior across strains, the relationship between C. elegans locomotive behavior and the number of muscle arms, for the first time, was investigated. A total of 128 worms of four C. elegans strains with different numbers of muscle arms were continuously tracked for 3 minutes per sample, and locomotive features were extracted on line. The potential impact of this research extends beyond revealing subtle phenotypic differences in C. elegans locomotive behavior across strains by demonstrating how automation techniques can be used to provide valuable tools for genetic investigations of C. elegans. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/COASE.2007.4341678 | 2007 IEEE International Conference on Automation Science and Engineering |
Keywords | Field | DocType |
micropositioning system,real-time feature extraction capability,locomotive behavior,image data recording,Gaussian pyramid level-2 images,cubic smoothing spline fitting,frequency 30 Hz | Computer vision,Data recording,Gaussian pyramid,Smoothing spline,Automation,Feature extraction,Artificial intelligence,Engineering,Image resolution,Mobile robot | Conference |
ISSN | ISBN | Citations |
2161-8070 | 978-1-4244-1153-5 | 0 |
PageRank | References | Authors |
0.34 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenhui Wang | 1 | 92 | 19.23 |
| Yu Sun | 2 | 418 | 69.89 |
| Scott J. Dixon | 3 | 2 | 0.71 |
| Mariam Alexander | 4 | 0 | 0.34 |
| Peter J. Roy | 5 | 0 | 0.34 |