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Automatic identification of Caenorhabditis elegans in population images by shape energy features

Daniel Ochoa Donoso (UGent) , Sidharta Gautama (UGent) and Wilfried Philips (UGent)
(2010) JOURNAL OF MICROSCOPY-OXFORD. 238(2). p.173-184
Author
Organization
Abstract
Experiments on model organisms are used to extend the understanding of complex biological processes. In Caenorhabditis elegans studies, populations of specimens are sampled to measure certain morphological properties and a population is characterized based on statistics extracted from such samples. Automatic detection of C. elegans in such culture images is a difficult problem. The images are affected by clutter, overlap and image degradations. In this paper, we exploit shape and appearance differences between C. elegans and non-C. elegans segmentations. Shape information is captured by optimizing a parametric open contour model on training data. Features derived from the contour energies are proposed as shape descriptors and integrated in a probabilistic framework. These descriptors are evaluated for C. elegans detection in culture images. Our experiments show that measurements extracted from these samples correlate well with ground truth data. These positive results indicate that the proposed approach can be used for quantitative analysis of complex nematode images.
Keywords
recognition, C. elegans, segmentation

Citation

Please use this url to cite or link to this publication:

MLA
Ochoa Donoso, Daniel, Sidharta Gautama, and Wilfried Philips. “Automatic Identification of Caenorhabditis Elegans in Population Images by Shape Energy Features.” JOURNAL OF MICROSCOPY-OXFORD 238.2 (2010): 173–184. Print.
APA
Ochoa Donoso, D., Gautama, S., & Philips, W. (2010). Automatic identification of Caenorhabditis elegans in population images by shape energy features. JOURNAL OF MICROSCOPY-OXFORD, 238(2), 173–184.
Chicago author-date
Ochoa Donoso, Daniel, Sidharta Gautama, and Wilfried Philips. 2010. “Automatic Identification of Caenorhabditis Elegans in Population Images by Shape Energy Features.” Journal of Microscopy-oxford 238 (2): 173–184.
Chicago author-date (all authors)
Ochoa Donoso, Daniel, Sidharta Gautama, and Wilfried Philips. 2010. “Automatic Identification of Caenorhabditis Elegans in Population Images by Shape Energy Features.” Journal of Microscopy-oxford 238 (2): 173–184.
Vancouver
1.
Ochoa Donoso D, Gautama S, Philips W. Automatic identification of Caenorhabditis elegans in population images by shape energy features. JOURNAL OF MICROSCOPY-OXFORD. 2010;238(2):173–84.
IEEE
[1]
D. Ochoa Donoso, S. Gautama, and W. Philips, “Automatic identification of Caenorhabditis elegans in population images by shape energy features,” JOURNAL OF MICROSCOPY-OXFORD, vol. 238, no. 2, pp. 173–184, 2010.
@article{762461,
  abstract     = {Experiments on model organisms are used to extend the understanding of complex biological processes. In Caenorhabditis elegans studies, populations of specimens are sampled to measure certain morphological properties and a population is characterized based on statistics extracted from such samples. Automatic detection of C. elegans in such culture images is a difficult problem. The images are affected by clutter, overlap and image degradations. In this paper, we exploit shape and appearance differences between C. elegans and non-C. elegans segmentations. Shape information is captured by optimizing a parametric open contour model on training data. Features derived from the contour energies are proposed as shape descriptors and integrated in a probabilistic framework. These descriptors are evaluated for C. elegans detection in culture images. Our experiments show that measurements extracted from these samples correlate well with ground truth data. These positive results indicate that the proposed approach can be used for quantitative analysis of complex nematode images.},
  author       = {Ochoa Donoso, Daniel and Gautama, Sidharta and Philips, Wilfried},
  issn         = {0022-2720},
  journal      = {JOURNAL OF MICROSCOPY-OXFORD},
  keywords     = {recognition,C. elegans,segmentation},
  language     = {eng},
  number       = {2},
  pages        = {173--184},
  title        = {Automatic identification of Caenorhabditis elegans in population images by shape energy features},
  url          = {http://dx.doi.org/10.1111/j.1365-2818.2009.03339.x},
  volume       = {238},
  year         = {2010},
}

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