Worm Analysis System

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There is a compelling need for improved software systems for delineating the C.elegans worms in time-lapse image sequences and tracking their movements. Segmentation and tracking provide the basis for making quantitative measurements of worm morphology, and various aspects of their dynamic behaviors.
 
 
 
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There is a compelling need for improved software systems for delineating the C.elegans worms in time-lapse image sequences and tracking their movements. Segmentation and tracking provide the basis for making quantitative measurements of worm morphology, and various aspects of their dynamic behaviors.
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== Worm Analysis System ==
 
== Worm Analysis System ==

Revision as of 04:03, 15 February 2010


There is a compelling need for improved software systems for delineating the C.elegans worms in time-lapse image sequences and tracking their movements. Segmentation and tracking provide the basis for making quantitative measurements of worm morphology, and various aspects of their dynamic behaviors.


Worm Analysis System

For information of our old worm project, please refer to [Old Worm Project].

References

  • [1] Yu Wang, Roysam Badrinath, “Joint Tracking and Locomotion State Recognition of C.elegans from Time-Lapse Image Sequences,” IEEE International Symposium on Biomedical Imaging (ISBI) 2010 (oral presentation).
  • [2] Roussel Nicolas, Morton Christine A, Finger Fern P, Roysam Badrinath, “A computational model for C. elegans locomotory behavior : Application to multiworm tracking,” IEEE transactions on biomedical engineering, pp. 1786-1797, 2007.
  • [3] Katsunori Hoshi, Ryuzo Shingai, “Computer-driven automatic identification of locomotion states in Caenorhabditis elegans,” J Neurosci Methods, vol. 157(2), pp.355-363, 2006.
  • [4] Huang KM, Cosman P, Schafer WR, “Machine vision based detection of omega bends and reversals in C. elegans,” Journal of Neuroscience Methods, vol. 158, Issue 2, pp. 323-336, 2006.
  • [5] Nicolas Roussel, "A Computational Model for C.elegans locomotory behavior: Application to Multi-Worm tracking", Phd Thesis, 2007.
  • [6] K.M. Huang, P.C. Cosman, and W. Schafer, “Automated tracking of multiple C. elegans with articulated models,” IEEE International Symposium on Biomedical Imaging (ISBI) 2007, pp. 1240-1243, 2007.
  • [7] Fontaine, E., Barr, A., Burdick, J. W., “Model-based tracking of multiple worms and fish,” ICCV Workshop on Dynamical Vision, 2007.
  • [8] Fontaine, E., Barr, A., Burdick, J. W., "Model-based tracking of multiple worms and fish", In ICCV Workshop on Dynamical Vision, 2007.
  • [9] Wei Geng; Cosman, P.; Berry, C.C.; Zhaoyang Feng; Schafer, W.R., “Automatic tracking, feature extraction and classification of C. elegans phenotypes,” Biomedical Engineering, IEEE Transactions on, vol.51, no.10, pp.1811-1820, 2004.
  • [10] Isard, M.; Blake, A., “A mixed-state condensation tracker with automatic model-switching,” Computer Vision, 1998. Sixth International Conference on, pp.107-112,1998.
  • [11] G.J. Stephens et al., "Dimensionality and Dynamics in the Behavior of C. elegans", PLoS Comp. Biol., 2008.
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