Abstract
Digital holographic microscopy can provide quantitative phase images (QPIs) of 3D profile of red blood cell (RBC) with nanometer accuracy. In this paper we propose applying k-means clustering method to cluster RBCs into two groups of young and old RBCs by using a four-dimensional feature vector. The features are RBC thickness average, surface area-volume ratio, sphericity coefficient and RBC perimeter that can be obtained from QPIs. The proposed features are related to the morphology of RBC. The experimental result shows that by utilizing the proposed method two groups of sphero-echinocytes (old RBCs) and non-spheroechinocytes RBCs can be perfectly clustered.
Original language | English |
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Title of host publication | Holography |
Subtitle of host publication | Advances and Modern Trends V |
Editors | John T. Sheridan, Miroslav Hrabovsky, Antonio Fimia |
Publisher | SPIE |
ISBN (Electronic) | 9781510609679 |
DOIs | |
State | Published - 2017 |
Event | Holography: Advances and Modern Trends V 2017 - Prague, Czech Republic Duration: 24 Apr 2017 → 27 Apr 2017 |
Publication series
Name | Proceedings of SPIE - The International Society for Optical Engineering |
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Volume | 10233 |
ISSN (Print) | 0277-786X |
ISSN (Electronic) | 1996-756X |
Conference
Conference | Holography: Advances and Modern Trends V 2017 |
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Country/Territory | Czech Republic |
City | Prague |
Period | 24/04/17 → 27/04/17 |
Bibliographical note
Publisher Copyright:© 2017 SPIE.
Keywords
- Clustering evaluation
- Digital holographic microscopy
- Old and new RBCs
- Red blood cell clustering