Optimization of a cell counting algorithm for mobile point-of-care testing platforms

Dae Han Ahn, Nam Sung Kim, Sang Jun Moon, Taejoon Park, Sang Hyuk Son

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)15244-15261
Number of pages18
JournalSensors (Switzerland)
Issue number8
StatePublished - Aug 19 2014
Externally publishedYes


  • Cell counting
  • Normalized cross-correlation
  • Point-of-care testing

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering


Dive into the research topics of 'Optimization of a cell counting algorithm for mobile point-of-care testing platforms'. Together they form a unique fingerprint.

Cite this