Automated statistical quantification of three-dimensional morphology and mean corpuscular hemoglobin of multiple red blood cells.

Détails

ID Serval
serval:BIB_435A2D9132F5
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Automated statistical quantification of three-dimensional morphology and mean corpuscular hemoglobin of multiple red blood cells.
Périodique
Optics Express
Auteur(s)
Moon I., Javidi B., Yi F., Boss D., Marquet P.
ISSN
1094-4087 (Electronic)
ISSN-L
1094-4087
Statut éditorial
Publié
Date de publication
2012
Peer-reviewed
Oui
Volume
20
Numéro
9
Pages
10295-10309
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov'tPublication Status: ppublish
Résumé
In this paper, we present an automated approach to quantify information about three-dimensional (3D) morphology, hemoglobin content and density of mature red blood cells (RBCs) using off-axis digital holographic microscopy (DHM) and statistical algorithms. The digital hologram of RBCs is recorded by a CCD camera using an off-axis interferometry setup and quantitative phase images of RBCs are obtained by a numerical reconstruction algorithm. In order to remove unnecessary parts and obtain clear targets in the reconstructed phase image with many RBCs, the marker-controlled watershed segmentation algorithm is applied to the phase image. Each RBC in the segmented phase image is three-dimensionally investigated. Characteristic properties such as projected cell surface, average phase, sphericity coefficient, mean corpuscular hemoglobin (MCH) and MCH surface density of each RBC is quantitatively measured. We experimentally demonstrate that joint statistical distributions of the characteristic parameters of RBCs can be obtained by our algorithm and efficiently used as a feature pattern to discriminate between RBC populations that differ in shape and hemoglobin content. Our study opens the possibility of automated RBC quantitative analysis suitable for the rapid classification of a large number of RBCs from an individual blood specimen, which is a fundamental step to develop a diagnostic approach based on DHM.
Mots-clé
Cells, Cultured, Data Interpretation, Statistical, Erythrocytes/metabolism, Hemoglobins/analysis, Hemoglobins/ultrastructure, Holography/methods, Humans, Image Interpretation, Computer-Assisted/methods, Imaging, Three-Dimensional/methods, Microscopy/methods
Pubmed
Web of science
Création de la notice
05/04/2013 9:52
Dernière modification de la notice
20/08/2019 13:47
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