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High-resolution cell outline segmentation and tracking from phase-contrast microscopy images


Ambühl, Mark E; Brepsant, Charles; Meister, Jean-Jacques; Verkhovsky, Alexander B; Sbalzarini, Ivo F (2011). High-resolution cell outline segmentation and tracking from phase-contrast microscopy images. Journal of Microscopy, 245(2):161-170.

Abstract

Accurate extraction of cell outlines from microscopy images is essential for analysing the dynamics of migrating cells. Phase-contrast microscopy is one of the most common and convenient imaging modalities for observing cell motility because it does not require exogenous labelling and uses only moderate light levels with generally negligible phototoxicity effects. Automatic extraction and tracking of high-resolution cell outlines from phase-contrast images, however, is difficult due to complex and non-uniform edge intensity. We present a novel image-processing method based on refined level-set segmentation for accurate extraction of cell outlines from high-resolution phase-contrast images. The algorithm is validated on synthetic images of defined noise levels and applied to real image sequences of polarizing and persistently migrating keratocyte cells. We demonstrate that the algorithm is able to reliably reveal fine features in the cell edge dynamics.

Accurate extraction of cell outlines from microscopy images is essential for analysing the dynamics of migrating cells. Phase-contrast microscopy is one of the most common and convenient imaging modalities for observing cell motility because it does not require exogenous labelling and uses only moderate light levels with generally negligible phototoxicity effects. Automatic extraction and tracking of high-resolution cell outlines from phase-contrast images, however, is difficult due to complex and non-uniform edge intensity. We present a novel image-processing method based on refined level-set segmentation for accurate extraction of cell outlines from high-resolution phase-contrast images. The algorithm is validated on synthetic images of defined noise levels and applied to real image sequences of polarizing and persistently migrating keratocyte cells. We demonstrate that the algorithm is able to reliably reveal fine features in the cell edge dynamics.

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20 citations in Web of Science®
25 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > LipidX
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2011
Deposited On:05 Jul 2013 12:28
Last Modified:05 Apr 2016 16:51
Publisher:Wiley-Blackwell
ISSN:0022-2720
Publisher DOI:https://doi.org/10.1111/j.1365-2818.2011.03558.x
Permanent URL: https://doi.org/10.5167/uzh-79221

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