Chrysalis: A New Method for High-Throughput Histo-Cytometry Analysis of Images and Movies
Author(s) -
Dmitri I. Kotov,
Thomas Pengo,
Jason S. Mitchell,
Matthew J. Gastinger,
Marc K. Jenkins
Publication year - 2018
Publication title -
the journal of immunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.737
H-Index - 372
eISSN - 1550-6606
pISSN - 0022-1767
DOI - 10.4049/jimmunol.1801202
Subject(s) - throughput , computer science , computer graphics (images) , artificial intelligence , computer vision , telecommunications , wireless
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.
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