Real-time high dynamic range laser scanning microscopy. Vinegoni, C., Leon Swisher, C., Fumene Feruglio, P., Giedt, R. J., Rousso, D. L., Stapleton, S., & Weissleder, R. Nature Communications, 7:11077, April, 2016. ![Real-time high dynamic range laser scanning microscopy [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.
@article{vinegoni_real-time_2016,
title = {Real-time high dynamic range laser scanning microscopy},
volume = {7},
copyright = {© 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
url = {http://www.nature.com/ncomms/2016/160401/ncomms11077/full/ncomms11077.html},
doi = {10.1038/ncomms11077},
abstract = {In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.},
language = {en},
urldate = {2016-04-04TZ},
journal = {Nature Communications},
author = {Vinegoni, C. and Leon Swisher, C. and Fumene Feruglio, P. and Giedt, R. J. and Rousso, D. L. and Stapleton, S. and Weissleder, R.},
month = apr,
year = {2016},
pages = {11077}
}
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