Image analysis in nonlinear microscopy

  • Hagmar J
  • Brackmann C
  • Gustavsson T
 et al. 
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Abstract

The ability to automatically extract quantitative data from nonlinear microscopy images is here explored, tak-ing 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 non-linear density dependence of the signal. Instead, the capability of four state-of-the-art image analysis algo-rithms was evaluated. Among these, local thresholding was found to be the widest applicable segmentation algorithm.

Author-supplied keywords

  • 1002960
  • 1804315
  • OCIS codes

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Authors

  • Jonas Hagmar

  • Christian Brackmann

  • Tomas Gustavsson

  • Annika Enejder

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