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Fluorescence microscopy tensor imaging representations for large-scale dataset analysis

Authors
Vinegoni, ClaudioFeruglio, Paolo FumeneCourties, GabrielSchmidt, StephenHulsmans, MaartenLee, SungonWang, RuiSosnovik, DavidNahrendorf, MatthiasWeissleder, Ralph
Issue Date
Mar-2020
Publisher
NATURE PUBLISHING GROUP
Citation
SCIENTIFIC REPORTS, v.10, no.1, pp 1 - 15
Pages
15
Indexed
SCIE
SCOPUS
Journal Title
SCIENTIFIC REPORTS
Volume
10
Number
1
Start Page
1
End Page
15
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1210
DOI
10.1038/s41598-020-62233-2
ISSN
2045-2322
Abstract
Understanding complex biological systems requires the system-wide characterization of cellular and molecular features. Recent advances in optical imaging technologies and chemical tissue clearing have facilitated the acquisition of whole-organ imaging datasets, but automated tools for their quantitative analysis and visualization are still lacking. We have here developed a visualization technique capable of providing whole-organ tensor imaging representations of local regional descriptors based on fluorescence data acquisition. This method enables rapid, multiscale, analysis and virtualization of large-volume, high-resolution complex biological data while generating 3D tractographic representations. Using the murine heart as a model, our method allowed us to analyze and interrogate the cardiac microvasculature and the tissue resident macrophage distribution and better infer and delineate the underlying structural network in unprecedented detail.
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