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Optimization of a Cell Counting Algorithm for Mobile Point-of-Care Testing Platforms
- Optimization of a Cell Counting Algorithm for Mobile Point-of-Care Testing Platforms
- Ahn, D[Ahn, DaeHan]; Kim, NS[Kim, Nam Sung]; Moon, S[Moon, SangJun]; Park, T[Park, Taejoon]; Son, SH[Son, Sang Hyuk]
- DGIST Authors
- Ahn, D[Ahn, DaeHan]; Moon, S[Moon, SangJun]; Park, T[Park, Taejoon]; Son, SH[Son, Sang Hyuk]
- Issue Date
- Sensors, 14(8), 15244-15261
- Article Type
- Algorithms; Attractive Solutions; Cell Counting; Energy Utilization; Normalized Cross-Correlation (NCC); Optimization Techniques; Optimized Algorithms; Original Algorithms; Point-of-Care Testing; Smartphones; Software Testing; Testing Platforms
- 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. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
- MDPI AG
- Related Researcher
Son, Sang Hyuk
RTCPS(Real-Time Cyber-Physical Systems Research) Lab
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