Image analysis in non-linear microscopy

• 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.

Ämnesord

NATURVETENSKAP  -- Biologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences (hsv//eng)

NATURVETENSKAP  -- Fysik -- Atom- och molekylfysik och optik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Atom and Molecular Physics and Optics (hsv//eng)

NATURVETENSKAP  -- Fysik -- Annan fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Other Physics Topics (hsv//eng)

NATURVETENSKAP  -- Biologi -- Zoologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Zoology (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

Yeast

Non-linear optics

Image analysis

C. elegans

CARS microscopy

Publikations- och innehållstyp

art (ämneskategori)

ref (ämneskategori)