| Literature DB >> 30510065 |
Dmitri I Kotov1,2, Thomas Pengo3, Jason S Mitchell4,5,6, Matthew J Gastinger7, Marc K Jenkins4,2.
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.Entities:
Mesh:
Year: 2018 PMID: 30510065 PMCID: PMC6310099 DOI: 10.4049/jimmunol.1801202
Source DB: PubMed Journal: J Immunol ISSN: 0022-1767 Impact factor: 5.422