Image analysis in nonlinear microscopy
JOSA A, Vol. 25, Issue 9, pp. 2195-2206 (2008)
http://dx.doi.org/10.1364/JOSAA.25.002195
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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.
© 2008 Optical Society of America
OCIS Codes
(100.2960) Image processing : Image analysis
(180.4315) Microscopy : Nonlinear microscopy
ToC Category:
Microscopy
History
Original Manuscript: March 17, 2008
Revised Manuscript: June 21, 2008
Manuscript Accepted: June 24, 2008
Published: August 6, 2008
Virtual Issues
Vol. 3, Iss. 11 Virtual Journal for Biomedical Optics
Citation
Jonas Hagmar, Christian Brackmann, Tomas Gustavsson, and Annika Enejder, "Image analysis in nonlinear microscopy," J. Opt. Soc. Am. A 25, 2195-2206 (2008)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-25-9-2195
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