Fluorescence microscopy tensor imaging representations for large-scale dataset analysis
- Authors
- Vinegoni, Claudio; Feruglio, Paolo Fumene; Courties, Gabriel; Schmidt, Stephen; Hulsmans, Maarten; Lee, Sungon; Wang, Rui; Sosnovik, David; Nahrendorf, Matthias; Weissleder, 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.
- Files in This Item
-
Go to Link
- Appears in
Collections - COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF ROBOT ENGINEERING > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1210)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.