Chrysalis: A new method for high-throughput histo-cytometry analysis of images and movies

Dmitri I. Kotov, Thomas Pengo, Jason S. Mitchell, Matthew J. Gastinger, Marc K. Jenkins

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Advances in imaging have led to the development of powerful multispectral, quantitative imaging techniques, like histo-cytometry. The utility of this approach is limited, however, by the need for time consuming manual image analysis.We therefore developed the software Chrysalis and a group of Imaris Xtensions to automate this process. The resulting automation allowed for high-throughput histo-cytometry analysis of three-dimensional confocal microscopy and two-photon time-lapse images of T cell-dendritic cell interactions in mouse spleens. It was also applied to epi-fluorescence images to quantify T cell localization within splenic tissue by using a "signal absorption" strategy that avoids computationally intensive distance measurements. In summary, this image processing and analysis software makes histo-cytometry more useful for immunology applications by automating image analysis.

Original languageEnglish (US)
Pages (from-to)300-308
Number of pages9
JournalJournal of Immunology
Volume202
Issue number1
DOIs
StatePublished - Jan 1 2019

Bibliographical note

Funding Information:
This work was supported by National Institutes of Health Grants T32 AI083196 and T32 AI007313 (to D.I.K.) and R01 AI039614 (to M.K.J.).

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural

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