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.
Mendeley saves you time finding and organizing research
There are no full text links
Choose a citation style from the tabs below