Automated analysis and classification of infected macrophages using bright-field amplitude contrast data

J Biomol Screen. 2012 Mar;17(3):401-8. doi: 10.1177/1087057111426902. Epub 2011 Nov 4.

Abstract

This article presents a methodology for acquisition and analysis of bright-field amplitude contrast image data in high-throughput screening (HTS) for the measurement of cell density, cell viability, and classification of individual cells into phenotypic classes. We present a robust image analysis pipeline, where the original data are subjected to image standardization, image enhancement, and segmentation by region growing. This work develops new imaging and analysis techniques for cell analysis in HTS and successfully addresses a particular need for direct measurement of cell density and other features without using dyes.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Cell Count
  • Cell Survival
  • Francisella tularensis
  • Humans
  • Image Enhancement / methods
  • Image Processing, Computer-Assisted / methods*
  • Macrophages / microbiology*
  • Microscopy / methods
  • Pattern Recognition, Automated / methods*
  • Phenotype
  • Tularemia / diagnosis*