Extracting 3D cell parameters from dense tissue environments: application to the development of the mouse heart. - Institut Pasteur Access content directly
Journal Articles Bioinformatics Year : 2013

Extracting 3D cell parameters from dense tissue environments: application to the development of the mouse heart.

Abstract

In developmental biology, quantitative tools to extract features from fluorescence microscopy images are becoming essential to characterize organ morphogenesis at the cellular level. However, automated image analysis in this context is a challenging task, owing to perturbations induced by the acquisition process, especially in organisms where the tissue is dense and opaque.
We propose an automated framework for the segmentation of 3D microscopy images of highly cluttered environments such as developing tissues. The approach is based on a partial differential equation framework that jointly takes advantage of the nuclear and cellular membrane information to enable accurate extraction of nuclei and cells in dense tissues. This framework has been used to study the developing mouse heart, allowing the extraction of quantitative information such as the cell cycle duration; the method also provides qualitative information on cell division and cell polarity through the creation of 3D orientation maps that provide novel insight into tissue organization during organogenesis.
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Dates and versions

pasteur-01572064 , version 1 (04-08-2017)

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Sorin Pop, Alexandre C Dufour, Jean-François Le Garrec, Chiara V Ragni, Clémire Cimper, et al.. Extracting 3D cell parameters from dense tissue environments: application to the development of the mouse heart.. Bioinformatics, 2013, 29 (6), pp.772-9. ⟨10.1093/bioinformatics/btt027⟩. ⟨pasteur-01572064⟩
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