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An Automated Method for Differential Blood Counting Using Microscope Color Image of Isolated WBC

An Automated Method for Differential Blood Counting Using Microscope Color Image of Isolated WBC

Anant R. Koppar, Venugopalachar Sridhar
Copyright: © 2012 |Pages: 14
ISBN13: 9781466609099|ISBN10: 1466609095|EISBN13: 9781466609105
DOI: 10.4018/978-1-4666-0909-9.ch017
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MLA

Koppar, Anant R., and Venugopalachar Sridhar. "An Automated Method for Differential Blood Counting Using Microscope Color Image of Isolated WBC." Emerging Communication Technologies for E-Health and Medicine, edited by Joel J.P.C. Rodrigues, IGI Global, 2012, pp. 219-232. https://doi.org/10.4018/978-1-4666-0909-9.ch017

APA

Koppar, A. R. & Sridhar, V. (2012). An Automated Method for Differential Blood Counting Using Microscope Color Image of Isolated WBC. In J. Rodrigues (Ed.), Emerging Communication Technologies for E-Health and Medicine (pp. 219-232). IGI Global. https://doi.org/10.4018/978-1-4666-0909-9.ch017

Chicago

Koppar, Anant R., and Venugopalachar Sridhar. "An Automated Method for Differential Blood Counting Using Microscope Color Image of Isolated WBC." In Emerging Communication Technologies for E-Health and Medicine, edited by Joel J.P.C. Rodrigues, 219-232. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-0909-9.ch017

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Abstract

Healthcare Delivery Systems are becoming overloaded in developed and developing countries. It is imperative that more efficient and cost effective processes be employed by innovative applications of technology in the delivery system. One such process in Haematology that needs attention is “Generation of report on the Differential Count of Blood”. Most rural centers in India still employ traditional, manual processes to identify and count White Blood Cells under a microscope. This traditional method of manually counting the white blood cells is prone to human error and time consuming. Medical Imaging with innovative application of algorithms can be used for recognizing and analyzing the images from blood smears to provide an efficient alternative for differential counting and reporting. In this regard, the objective of this paper is to provide a simple and pragmatic software system built on innovative yet simple imaging algorithms for achieving better efficiency and accuracy of results. The resulting work-flow process has enabled truly practical tele-pathology by enabling e-collaboration between lesser skilled technicians and more skilled experts, which cuts down the total turnaround time for differential count reporting from days to minutes. The system can be extended to detect malarial parasites in blood and also cancerous cells.

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