ChipSeg: an automatic tool to segment bacterial and mammalian cells cultured in microfluidic devices

Irene De Cesare, Criseida G Zamora Chimal, Lorena Postiglione, Mahmoud Khazim, Elisa Pedone, Barbara M Shannon, Gianfranco Fiore, Giansimone Perrino, Sara Napolitano, Diego di Bernardo, Nigel J Savery, Claire S Grierson, Mario Di Bernardo, Lucia Marucci

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Extracting quantitative measurements from time-lapse images is necessary in external feedback control applications, where segmentation results are used to inform control algorithms. We describe ChipSeg, a computational tool to segment bacterial and mammalian cells cultured in microfluidic devices and imaged by time-lapse microscopy, which can be used also in the context of external feedback control. The method is based on thresholding and uses the same core functions for both cell types. It allows to segment individual cells in high cell-density microfluidic devices, to quantify fluorescence protein expression over a time-lapse experiment and to track individual mammalian cells. ChipSeg enables robust segmentation in external feedback control experiments and can be easily customised for other experimental settings and research aims.
Original languageEnglish
JournalACS Omega
Publication statusAccepted/In press - 20 Nov 2020

Structured keywords

  • BrisSynBio
  • Bristol BioDesign Institute

Keywords

  • image analysis
  • segmentation
  • live-cell imaging
  • microfluidics
  • external feedback control

Cite this