Title |
SHERPA: an image segmentation and outline feature extraction tool for diatoms and other objects
|
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Published in |
BMC Bioinformatics, June 2014
|
DOI | 10.1186/1471-2105-15-218 |
Pubmed ID | |
Authors |
Michael Kloster, Gerhard Kauer, Bánk Beszteri |
Abstract |
Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and/or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Norway | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Netherlands | 2 | 2% |
Brazil | 1 | 1% |
United Kingdom | 1 | 1% |
Canada | 1 | 1% |
Spain | 1 | 1% |
Unknown | 75 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 22% |
Student > Ph. D. Student | 13 | 16% |
Student > Master | 13 | 16% |
Student > Bachelor | 12 | 15% |
Student > Postgraduate | 4 | 5% |
Other | 6 | 7% |
Unknown | 15 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 26 | 32% |
Earth and Planetary Sciences | 14 | 17% |
Engineering | 9 | 11% |
Computer Science | 5 | 6% |
Environmental Science | 3 | 4% |
Other | 7 | 9% |
Unknown | 17 | 21% |