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Journal articles
Sci. Rep.
Fluorescence microscopy tensor imaging representations for large-scale dataset analysis
Vinegoni#†, C.,
Feruglio†, P. F.,
Courties, G.,
Schmidt, S.,
Hulsmans, M.,
Lee, S.,
Wang, R.,
Sosnovik, D.,
Nahrendorf, M.,
and Weissleder, R.
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.
32221334
PMC7101442
10.1038/s41598-020-62233-2
Proceedings papers
2020-BIBE
Video-rate acquisition fluorescence microscopy via generative adversarial networks
Issa, T.B.,
Vinegoni, C.,
Shaw, A.,
Feruglio, P.F.,
Weissleder, R.,
and Uminsky, D.
In 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) 2020