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.
Bibliographical noteFunding 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.).
© 2018 by The American Association of Immunologists, Inc.
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural