Image analysis in nonlinear microscopy |
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Authors: | Hagmar Jonas Brackmann Christian Gustavsson Tomas Enejder Annika |
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Affiliation: | Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenberg, Sweden. |
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Abstract: | The ability to automatically extract quantitative data from nonlinear microscopy images is here explored, taking nonlinear and coherent effects into account. Objects of different degrees of complexity were investigated: theoretical images of spherical objects, experimentally collected coherent anti-Stokes Raman scattering images of polystyrene spheres in background-generating agar, well-separated lipid droplets in living yeast cells, and conglomerations of lipid droplets in living C. elegans nematodes. The in linear microscopy useful measure of full width at half-maximum (FWHM) was shown to provide inadequate measures of object size due to the nonlinear density dependence of the signal. Instead, the capability of four state-of-the-art image analysis algorithms was evaluated. Among these, local thresholding was found to be the widest applicable segmentation algorithm. |
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