Clustering of red blood cells using digital holographic microscopy

K. Jaferzadeh, E. Ahmadzadeh, I. Moon, S. Gholami

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationHolography
Subtitle of host publicationAdvances and Modern Trends V
EditorsJohn T. Sheridan, Miroslav Hrabovsky, Antonio Fimia
PublisherSPIE
ISBN (Electronic)9781510609679
DOIs
StatePublished - 2017
EventHolography: Advances and Modern Trends V 2017 - Prague, Czech Republic
Duration: 24 Apr 201727 Apr 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10233
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceHolography: Advances and Modern Trends V 2017
Country/TerritoryCzech Republic
CityPrague
Period24/04/1727/04/17

Bibliographical note

Publisher Copyright:
© 2017 SPIE.

Keywords

  • Clustering evaluation
  • Digital holographic microscopy
  • Old and new RBCs
  • Red blood cell clustering

Fingerprint

Dive into the research topics of 'Clustering of red blood cells using digital holographic microscopy'. Together they form a unique fingerprint.

Cite this