Fast globally optimal segmentation of cells in fluorescence microscopy images

Med Image Comput Comput Assist Interv. 2011;14(Pt 1):645-52. doi: 10.1007/978-3-642-23623-5_81.

Abstract

Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Cell Biology
  • Cell Nucleus / metabolism*
  • Diagnostic Imaging / methods
  • Fluorescent Dyes / pharmacology
  • Image Processing, Computer-Assisted
  • Mice
  • Microscopy, Fluorescence / methods*
  • Models, Statistical
  • Models, Theoretical
  • NIH 3T3 Cells
  • Pattern Recognition, Automated / methods
  • Reproducibility of Results

Substances

  • Fluorescent Dyes