Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data

Amelia G. White, Patricia G. Cipriani, Huey Ling Kao, Brandon Lees, Davi Geiger, Eduardo Sontag, Kristin C. Gunsalus, Fabio Piano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a hierarchical principle for object recognition and its application to automatically classify developmental stages of C. elegans animals from a population of mixed stages. The object recognition machine consists of four hierarchical layers, each composed of units upon which evaluation functions output a label score, followed by a grouping mechanism that resolves ambiguities in the score by imposing local consistency constraints. Each layer then outputs groups of units, from which the units of the next layer are derived. Using this hierarchical principle, the machine builds up successively more sophisticated representations of the objects to be classified. The algorithm segments large and small objects, decomposes objects into parts, extracts features from these parts, and classifies them by SVM. We are using this system to analyze phenotypic data from C. elegans high-throughput genetic screens, and our system overcomes a previous bottleneck in image analysis by achieving near real-time scoring of image data. The system is in current use in a functioning C. elegans laboratory and has processed over two hundred thousand images for lab users.

Original languageEnglish (US)
Title of host publication2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Pages3089-3096
Number of pages8
DOIs
StatePublished - 2010
Event2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, United States
Duration: Jun 13 2010Jun 18 2010

Other

Other2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
CountryUnited States
CitySan Francisco, CA
Period6/13/106/18/10

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Object recognition
Throughput
Function evaluation
Image analysis
Labels
Animals

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

White, A. G., Cipriani, P. G., Kao, H. L., Lees, B., Geiger, D., Sontag, E., ... Piano, F. (2010). Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 (pp. 3089-3096). [5540065] https://doi.org/10.1109/CVPR.2010.5540065

Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data. / White, Amelia G.; Cipriani, Patricia G.; Kao, Huey Ling; Lees, Brandon; Geiger, Davi; Sontag, Eduardo; Gunsalus, Kristin C.; Piano, Fabio.

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. p. 3089-3096 5540065.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

White, AG, Cipriani, PG, Kao, HL, Lees, B, Geiger, D, Sontag, E, Gunsalus, KC & Piano, F 2010, Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010., 5540065, pp. 3089-3096, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, United States, 6/13/10. https://doi.org/10.1109/CVPR.2010.5540065
White AG, Cipriani PG, Kao HL, Lees B, Geiger D, Sontag E et al. Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. p. 3089-3096. 5540065 https://doi.org/10.1109/CVPR.2010.5540065
White, Amelia G. ; Cipriani, Patricia G. ; Kao, Huey Ling ; Lees, Brandon ; Geiger, Davi ; Sontag, Eduardo ; Gunsalus, Kristin C. ; Piano, Fabio. / Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. pp. 3089-3096
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