NDLI: A System for Counting Fetal and Maternal Red Blood Cells

Content Provider	IEEE Xplore Digital Library
Author	Ji Ge Zheng Gong Jun Chen Jun Liu Nguyen, J. Zongyi Yang Chen Wang Yu Sun
Copyright Year	1964
Abstract	The Kleihauer-Betke (KB) test is the standard method for quantitating fetal-maternal hemorrhage in maternal care. In hospitals, the KB test is performed by a certified technologist to count a minimum of 2000 fetal and maternal red blood cells (RBCs) on a blood smear. Manual counting suffers from inherent inconsistency and unreliability. This paper describes a system for automated counting and distinguishing fetal and maternal RBCs on clinical KB slides. A custom-adapted hardware platform is used for KB slide scanning and image capturing. Spatial-color pixel classification with spectral clustering is proposed to separate overlapping cells. Optimal clustering number and total cell number are obtained through maximizing cluster validity index. To accurately identify fetal RBCs from maternal RBCs, multiple features including cell size, roundness, gradient, and saturation difference between cell and whole slide are used in supervised learning to generate feature vectors, to tackle cell color, shape, and contrast variations across clinical KB slides. The results show that the automated system is capable of completing the counting of over 60 000 cells (versus ~2000 by technologists) within 5 min (versus ~15 min by technologists). The throughput is improved by approximately 90 times compared to manual reading by technologists. The counting results are highly accurate and correlate strongly with those from benchmarking flow cytometry measurement.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Starting Page	2823
Ending Page	2829
Page Count	7
File Size	1357942
File Format	PDF
ISSN	00189294
Volume Number	61
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image color analysis Image segmentation Clustering methods Red blood cells Supervised learning Throughput Blood maternal red blood cells Automation fetal-maternal hemorrhage (FMH) quantification fetal red blood cells image processing Kleihauer–Betke (KB) test
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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A system for automated counting of fetal and maternal red blood cells in clinical KB test

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