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Proceedings Paper

Field performance of a low-cost and fully-automated blood counting system operated by trained and untrained users (Conference Presentation)
Author(s): Dengling Xie; Yanjun Xie; Peng Liu; Lieshu Tong; Kaiqin Chu; Zachary J. Smith
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Paper Abstract

Current flow-based blood counting devices require expensive and centralized medical infrastructure and are not appropriate for field use. In this paper we report a method to count red blood cells, white blood cells as well as platelets through a low-cost and fully-automated blood counting system. The approach consists of using a compact, custom-built microscope with large field-of-view to record bright-field and fluorescence images of samples that are diluted with a single, stable reagent mixture and counted using automatic algorithms. Sample collection is performed manually using a spring loaded lancet, and volume-metering capillary tubes. The capillaries are then dropped into a tube of pre-measured reagents and gently shaken for 10-30 seconds. The sample is loaded into a measurement chamber and placed on a custom 3D printed platform. Sample translation and focusing is fully automated, and a user has only to press a button for the measurement and analysis to commence. Cost of the system is minimized through the use of custom-designed motorized components. We performed a series of comparative experiments by trained and untrained users on blood from adults and children. We compare the performance of our system, as operated by trained and untrained users, to the clinical gold standard using a Bland-Altman analysis, demonstrating good agreement of our system to the clinical standard. The system’s low cost, complete automation, and good field performance indicate that it can be successfully translated for use in low-resource settings where central hematology laboratories are not accessible.

Paper Details

Date Published: 24 April 2017
PDF: 1 pages
Proc. SPIE 10072, Optical Diagnostics and Sensing XVII: Toward Point-of-Care Diagnostics, 100720H (24 April 2017); doi: 10.1117/12.2250685
Show Author Affiliations
Dengling Xie, Univ. of Science and Technology of China (China)
Yanjun Xie, Univ. of Science and Technology of China (China)
Peng Liu, Univ. of Science and Technology of China (China)
Lieshu Tong, Univ. of Science and Technology of China (China)
Kaiqin Chu, Univ. of Science and Technology of China (China)
Zachary J. Smith, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 10072:
Optical Diagnostics and Sensing XVII: Toward Point-of-Care Diagnostics
Gerard L. Coté, Editor(s)

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