Proc. SPIE. 10233, Holography: Advances and Modern Trends V
KEYWORDS: Internet, Microscopes, Holography, Principal component analysis, Digital holography, Tissues, Blood, Stereoscopy, Microscopy, 3D metrology, Reconstruction algorithms, Phase measurement, 3D displays, 3D image processing
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.