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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Restif, C. Ibanez-Ventoso, C. Driscoll, M. Metaxas, D. |
| Copyright Year | 2011 |
| Description | Author affiliation: Center for Computational Biomedicine Imaging and Modeling, Rutgers, New Jersey, USA (Restif, C.; Metaxas, D.) || Department of Molecular Biology and Biochemistry, Rutgers, New Jersey, USA (Ibanez-Ventoso, C.; Driscoll, M.) |
| Abstract | The model organism C. elegans is widely used for phenotype studies, where the behaviors of large numbers of individuals have to be measured accurately. Swimming motions exhibit unique aspects of their behavior, but are significantly more difficult to track than crawling motions. Filming multiple worms is necessary for high-throughput phenotype experiments, but adds to the complexity of tracking. Here we present a novel method to segment and track multiple swimming worms. Segmentation is done by low-level-vision processing followed by articulated model fitting. Tracking is performed by iteratively adjusting the articulated models to the successive frames. We tested our method on 404 videos and 2020 worms, and report results of 94.1% of worms tracked, which are valid 92.1% of the time. The models we use enable a cheap computation of a variety of measures of behavior. We report a quantitative comparison of three mutants using existing and novel phenotype measures, showing statistically significant differences of behavior. |
| Starting Page | 1542 |
| Ending Page | 1548 |
| File Size | 1078884 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424441273 |
| ISSN | 19457928 |
| DOI | 10.1109/ISBI.2011.5872695 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-03-30 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Grippers Videos Pixel Computational modeling Tracking Extremities Image segmentation Phenotyping Segmentation C. elegans Articulated model |
| Content Type | Text |
| Resource Type | Article |
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