Image analysis in non-linear microscopy
Artikel i vetenskaplig tidskrift, 2008

The ability to automatically extract quantitative data from non-linear microscopy images is here explored, taking their non-linear character into account. Objects of different degree 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 the non-linear 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.

Yeast

Non-linear optics

Image analysis

C. elegans

CARS microscopy

Författare

Jonas Hagmar

Christian Brackmann

Chalmers, Kemi- och bioteknik, Molekylär mikroskopi

Tomas Gustavsson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

Annika Enejder

Chalmers, Kemi- och bioteknik, Molekylär mikroskopi

Journal of Optical Society of America

Vol. 25 2195-2206

Ämneskategorier

Biologiska vetenskaper

Atom- och molekylfysik och optik

Annan fysik

Zoologi

Datorseende och robotik (autonoma system)