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dc.contributor.authorMoberg, Emily A.  Concept link
dc.contributor.authorSosik, Heidi M.  Concept link
dc.date.accessioned2014-05-09T15:15:17Z
dc.date.available2014-05-09T15:15:17Z
dc.date.issued2012-04
dc.identifier.citationLimnology and Oceanography: Methods 10 (2012): 278-288en_US
dc.identifier.urihttps://hdl.handle.net/1912/6619
dc.descriptionAuthor Posting. © Association for the Sciences of Limnology and Oceanography, 2012. This article is posted here by permission of Association for the Sciences of Limnology and Oceanography for personal use, not for redistribution. The definitive version was published in Limnology and Oceanography: Methods 10 (2012): 278-288, doi:10.4319/lom.2012.10.278.en_US
dc.description.abstractWe describe and evaluate an algorithm that uses a distance map to automatically calculate the biovolume of a planktonic organism from its two-dimensional boundary. Compared with existing approaches, this algorithm dramatically increases the speed and accuracy of biomass estimates from plankton images, and is thus especially suited for use with automated cell imaging technologies that produce large quantities of data. The algorithm operates on a two-dimensional image processed to identify organism boundaries. First, the distance of each interior pixel to the nearest boundary is calculated; next these same distances are assumed to apply for projection in the third dimension; and finally the resulting volume is adjusted by a multiplicative factor assuming locally circular cross-sections in the third dimension. Other cross-sectional shape factors can be applied as needed. In this way, the simple, computationally efficient, volume calculation can be refined to include taxon-specific shape information if available. We show that compared to traditional manual microscopic analysis, the distance map algorithm is unbiased and accurate (mean difference = -0.25%, standard deviation = 17%) for a range of cell morphologies, including those with concave boundaries that deviate from simple geometric shapes and whose volumes are not well represented by a solid of revolution around a single axis. Automated calculation of cell volumes can now be implemented with a combination of this new distance map algorithm for complex shapes and the solid of revolution approach for simple shapes, with an automated decision criterion to choose the appropriate approach for each image.en_US
dc.description.sponsorshipThis research was supported by grants (to HMS) from the Gordon and Betty Moore Foundation and NASA’s Ocean Biology and Biogeochemistry program, and a Woods Hole Oceanographic Institution Summer Student Fellow award (to EAM).en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.publisherAssociation for the Sciences of Limnology and Oceanographyen_US
dc.relation.urihttps://doi.org/10.4319/lom.2012.10.278
dc.titleDistance maps to estimate cell volume from two-dimensional plankton imagesen_US
dc.typeArticleen_US
dc.identifier.doi10.4319/lom.2012.10.278


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