Research Papers: Imaging

Automated segmentation of multiple red blood cells with digital holographic microscopy

[+] Author Affiliations
Faliu Yi, Inkyu Moon

Chosun University, School of Computer Engineering, 375 Seosuk-dong, Dong-gu, Gwangju, 501-759 Republic of Korea

Bahram Javidi

University of Connecticut, Department of Electrical and Computer Engineering U-2157, Storrs, Connecticut 06269-2157

Daniel Boss

LNDC, BMI, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

Pierre Marquet

LNDC, BMI, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

Département de Psychiatrie DPCHUV, Centre de Neurosciences Psychiatriques, PrillyLausanne, Switzerland

J. Biomed. Opt. 18(2), 026006 (Feb 01, 2013). doi:10.1117/1.JBO.18.2.026006
History: Received August 7, 2012; Revised December 25, 2012; Accepted January 4, 2013
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Abstract.  We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.

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© 2013 Society of Photo-Optical Instrumentation Engineers

Citation

Faliu Yi ; Inkyu Moon ; Bahram Javidi ; Daniel Boss and Pierre Marquet
"Automated segmentation of multiple red blood cells with digital holographic microscopy", J. Biomed. Opt. 18(2), 026006 (Feb 01, 2013). ; http://dx.doi.org/10.1117/1.JBO.18.2.026006


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