Optimization of a Cell Counting Algorithm for Mobile Point-of-Care Testing Platforms

Sensors

DaeHan Ahn¹  Nam Sung Kim²  SangJun Moon³  Taejoon Park¹ 

[1] Real-Time Cyber-Physical System Laboratory, Daegu Gyeoungbuk Institute of Science and Technology (DGIST), Daegu 711-873, Korea; E-Mails:;Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA; E-Mail:;Cybernetics Laboratory, Daegu Gyeoungbuk Institute of Science and Technology (DGIST), Daegu 711-873, Korea; E-Mail:

关键词: cell counting;    point-of-care testing;    normalized cross-correlation;   

DOI  :  10.3390/s140815244

来源: mdpi

【 摘 要 】

In a point-of-care (POC) setting, it is critically important to reliably count the number of specific cells in a blood sample. Software-based cell counting, which is far faster than manual counting, while much cheaper than hardware-based counting, has emerged as an attractive solution potentially applicable to mobile POC testing. However, the existing software-based algorithm based on the normalized cross-correlation (NCC) method is too time- and, thus, energy-consuming to be deployed for battery-powered mobile POC testing platforms. In this paper, we identify inefficiencies in the NCC-based algorithm and propose two synergistic optimization techniques that can considerably reduce the runtime and, thus, energy consumption of the original algorithm with negligible impact on counting accuracy. We demonstrate that an Android™ smart phone running the optimized algorithm consumes 11.5× less runtime than the original algorithm.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.