Algorithms for the Automated Analysis of Cellular Dynamics Within Living Fungal Colonies

N. C. Angarita-Jaimes, M. G. Roca M., C. E. Towers, N. D. Read, D. P. Towers

Research output: Contribution to journalArticlepeer-review

Abstract

We present robust and efficient algorithms to automate the measurement of nuclear movement and germ tube extension rates in living fungal networks. The aim is to facilitate the understanding of the dynamics and regulation of nuclear migration in growing fungal colonies. The proposed methodology combines a cascade correlation filter to identify nuclear centers from which 2D nuclear velocities are determined and a level set algorithm for centerline extraction to monitor spore (conidial) germling growth. We show how the proposed cascaded filter improves spatial resolution in the presence of noise and is robust when fluorescently labeled nuclei with different intensities are in close proximity to each other. The performance of the filter is evaluated by simulation in comparison to the well known Rayleigh and Sparrow criteria, and experimental evidence is given from clusters of nuclei and nuclei undergoing mitotic division. The capabilities developed have enabled the robust and objective analysis of 10's of Gigabytes of image data that is being exploited by biological scientists. (C) 2009 International Society for Advancement of Cytometry
Original languageEnglish
Pages (from-to)768-780
Number of pages13
JournalCytometry Part A
Volume75A
Issue number9
Early online date13 Aug 2009
DOIs
Publication statusPublished - 1 Sep 2009

Keywords

  • biological image processing
  • nuclei segmentation
  • super-resolution
  • nuclei tracking
  • correlation filter
  • germling growth rate
  • conidial anastomosis tubes

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