A robust algorithm for segmenting and tracking clustered cells in time-lapse fluorescent microscopy

IEEE J Biomed Health Inform. 2013 Jul;17(4):862-9. doi: 10.1109/JBHI.2013.2262233.

Abstract

We present herein a robust algorithm for cell tracking in a sequence of time-lapse 2-D fluorescent microscopy images. Tracking is performed automatically via a multiphase active contours algorithm adapted to the segmentation of clustered nuclei with obscure boundaries. An ellipse fitting method is applied to avoid problems typically associated with clustered, overlapping, or dying cells, and to obtain more accurate segmentation and tracking results. We provide quantitative validation of results obtained with this new algorithm by comparing them to the results obtained from the established CellProfiler, MTrack2 (plugin for Fiji), and LSetCellTracker software.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Cell Nucleus / physiology
  • Cell Tracking / methods*
  • HeLa Cells
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Microscopy, Fluorescence / methods*
  • Time-Lapse Imaging / methods*