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Edge detection, three‐dimensional cell boundary reconstruction and volume and surface area estimation from differential interference contrast images
Author(s) -
KENYON C. M.,
YANAI M.,
MACKLEM P. T.
Publication year - 1994
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.1994.tb03509.x
Subject(s) - differential interference contrast microscopy , optics , focus (optics) , contrast (vision) , interference (communication) , detector , voxel , enhanced data rates for gsm evolution , physics , microscopy , edge detection , noise (video) , materials science , biological system , artificial intelligence , computer science , image processing , image (mathematics) , biology , computer network , channel (broadcasting)
Summary Three‐dimensional (3‐D) cell morphology is important for the understanding of cell function and can by quantified in terms of volume and surface area. Differential interference contrast (DIC, or Nomarski) imaging can enable cell edges to be clearly visualized in unstained tissue due to the slight difference in refractive index between aqueous media and cytoplasm. DIC is affected in only one direction ‐ the direction of the optical shear. A 1‐D edge detector was used in that direction with a scale length equal to that of an in‐focus edge to highlight cell boundaries. By comparison with the signal from the edge detector on an out‐of‐focus slice, the in‐focus slices could be segmented and, after noise suppression, cell outlines obtained. A voxel paradigm was used to calculate cell volume and differential geometry was used for surface area estimation. We applied this approach to obtain 3‐D dimensional information by optical sectioning of motile Amoeba proteus .