5 Scopus citations

Abstract

The development of digital microscopy and computational power is providing new opportunities for analyzing the motility of the vesicles (proteins) within living cells. In this paper, an automatic method is developed to segment and track vesicles in large amount of fluorescence images, in order to compute a number of quantitative parameters such as displacement, residence time, binding, or immobile fraction. We present a method that permits the automatic tracking of subcellular structures in long sequences of fluorescence images (up to 100 frames). The method we propose has been tested on 92 data sets totaling 8225 frames.

Original languageEnglish
Pages (from-to)1364-1371
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5370 II
DOIs
StatePublished - 2004
EventProgress in Biomedical Optics and Imaging - Medical Imaging 2004: Imaging Processing - San Diego, CA, United States
Duration: Feb 16 2004Feb 19 2004

Keywords

  • Image segmentation
  • Motion model
  • Tracking algorithm
  • Weighted similarity measurement

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