<div class="csl-bib-body">
<div class="csl-entry">Becker, K., & Saghafi, S. (2024, June 29). <i>NeuroDeblur: A novel software for fast deconvolution of large light-sheet, confocal, or bright-field microscopy stacks</i> [Poster Presentation]. FENS 2024, Vienna, Austria.</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/199885
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dc.description.abstract
We developed a novel deconvolution software (NeuroDeblur), which significantly enhances the visibility of minute details, such as neurons
or nerve fibres, in large image stacks captured by light-sheet, confocal, or bright-field microscopy. NeuroDeblur employs synthetic point spread functions
tailored to each of these imaging modalities by utilizing a sophisticated optical model of the imaging procesess. Experimental point spread functions
derived from recordings of fluorescent beads can be used additionally. The software features a sophisticated adaptive background removal algorithm and
automatic block-wise processing of large data sets, enabling the handling of very large image stacks (>100 GB) even on modest computers equipped with 8
or 16 GB RAM. Through extensive parallelization and optional GPU acceleration, NeuroDeblur achieves high-speed performance. For instance, on a PC
equipped with a state-of-the-art NVidia graphics board, a 3D-stack comprising approximately 1 billion voxels can be deconvolved within 5-10 minutes.
en
dc.description.sponsorship
Technische Universität Wien
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dc.language.iso
en
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dc.subject
deconvolution
en
dc.subject
image processing
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dc.subject
light-sheet microscopy
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dc.subject
confocal microscopy
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dc.title
NeuroDeblur: A novel software for fast deconvolution of large light-sheet, confocal, or bright-field microscopy stacks
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dc.type
Presentation
en
dc.type
Vortrag
de
dc.relation.grantno
Software
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dc.type.category
Poster Presentation
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tuw.project.title
Weiterentwicklung und Kommerzialisierung einer Software zur Nachbearbeitung mikroskopischer Bilder mittels Dekonvolution
