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Quantitative 3D characterization of cellular materials: Segmentation and morphology of foam


Mader, Kevin; Mokso, Rajmund; Raufaste, Christophe; Dollet, Benjamin; Santucci, Stéphane; Lambert, Jérôme; Stampanoni, Marco (2012). Quantitative 3D characterization of cellular materials: Segmentation and morphology of foam. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 415:230-238.

Abstract

Wood, trabecular bone, coral, liquid foams, grains in polycrystals, igneous rock, and even many types of food share many structural similarities and belong to the general class called cellular materials. The visualization of these materials in 3D has been made possible in the last decades through a variety of imaging techniques including magnetic resonance imaging (MRI), micro-computed X-ray tomography (μCT), and confocal microscopy. Recent advances in synchrotron-based ultra fast tomography have enabled measurements in liquid foams with thousands of bubbles and time resolutions down to 0.5 s. Post-processing techniques have, however, not kept pace and extracting useful physical metrics from such measurements is far from trivial. In this manuscript we present and validate a new, fully-automated method for segmenting and labeling the void space in cellular materials where the walls between cells are not visible or present. The individual cell labeling is based on a new tool, the Gradient Guided Watershed, which, while computationally simple, can be robustly scaled to large data-sets. Specifically we demonstrate the utility of this new method on several liquid foams (with varying liquid fraction and polydispersity) composed of thousands of bubbles, and the subsequent quantitative 3D structural characterization of those foams.

Wood, trabecular bone, coral, liquid foams, grains in polycrystals, igneous rock, and even many types of food share many structural similarities and belong to the general class called cellular materials. The visualization of these materials in 3D has been made possible in the last decades through a variety of imaging techniques including magnetic resonance imaging (MRI), micro-computed X-ray tomography (μCT), and confocal microscopy. Recent advances in synchrotron-based ultra fast tomography have enabled measurements in liquid foams with thousands of bubbles and time resolutions down to 0.5 s. Post-processing techniques have, however, not kept pace and extracting useful physical metrics from such measurements is far from trivial. In this manuscript we present and validate a new, fully-automated method for segmenting and labeling the void space in cellular materials where the walls between cells are not visible or present. The individual cell labeling is based on a new tool, the Gradient Guided Watershed, which, while computationally simple, can be robustly scaled to large data-sets. Specifically we demonstrate the utility of this new method on several liquid foams (with varying liquid fraction and polydispersity) composed of thousands of bubbles, and the subsequent quantitative 3D structural characterization of those foams.

Citations

13 citations in Web of Science®
13 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Biomedical Engineering
Dewey Decimal Classification:170 Ethics
610 Medicine & health
Language:English
Date:2012
Deposited On:23 Jan 2013 12:42
Last Modified:05 Apr 2016 16:19
Publisher:Elsevier
ISSN:0927-7757
Publisher DOI:https://doi.org/10.1016/j.colsurfa.2012.09.007

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