Automated three-dimensional morphology-based clustering of human erythrocytes with regular shapes: stomatocytes, discocytes, and echinocytes

Ezat Ahmadzadeh; Keyvan Jaferzadeh; Jieun Lee; Inkyu Moon

doi:10.1117/1.JBO.22.7.076015

25 July 2017 Automated three-dimensional morphology-based clustering of human erythrocytes with regular shapes: stomatocytes, discocytes, and echinocytes

Ezat Ahmadzadeh, Keyvan Jaferzadeh, Jieun Lee, Inkyu Moon

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Journal of Biomedical Optics, Vol. 22, Issue 7, 076015 (July 2017). https://doi.org/10.1117/1.JBO.22.7.076015

Abstract

We present unsupervised clustering methods for automatic grouping of human red blood cells (RBCs) extracted from RBC quantitative phase images obtained by digital holographic microscopy into three RBC clusters with regular shapes, including biconcave, stomatocyte, and sphero-echinocyte. We select some good features related to the RBC profile and morphology, such as RBC average thickness, sphericity coefficient, and mean corpuscular volume, and clustering methods, including density-based spatial clustering applications with noise, k-medoids, and k-means, are applied to the set of morphological features. The clustering results of RBCs using a set of three-dimensional features are compared against a set of two-dimensional features. Our experimental results indicate that by utilizing the introduced set of features, two groups of biconcave RBCs and old RBCs (suffering from the sphero-echinocyte process) can be perfectly clustered. In addition, by increasing the number of clusters, the three RBC types can be effectively clustered in an automated unsupervised manner with high accuracy. The performance evaluation of the clustering techniques reveals that they can assist hematologists in further diagnosis.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Ezat Ahmadzadeh, Keyvan Jaferzadeh, Jieun Lee, and Inkyu Moon "Automated three-dimensional morphology-based clustering of human erythrocytes with regular shapes: stomatocytes, discocytes, and echinocytes," Journal of Biomedical Optics 22(7), 076015 (25 July 2017). https://doi.org/10.1117/1.JBO.22.7.076015

Received: 29 March 2017; Accepted: 5 July 2017; Published: 25 July 2017

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