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BigStitcher: Reconstructing high-resolution image datasets of cleared and expanded samples

Item Type:Preprint
Title:BigStitcher: Reconstructing high-resolution image datasets of cleared and expanded samples
Creators Name:Hörl, D. and Rojas Rusak, F. and Preusser, F. and Tillberg, P. and Randel, N. and Chhetri, R.K. and Cardona, A. and Keller, P.J. and Harz, H. and Leonhardt, H. and Treier, M. and Preibisch, S.
Abstract:New methods for clearing and expansion of biological objects create large, transparent samples that can be rapidly imaged using light-sheet microscopy. Resulting image acquisitions are terabytes in size and consist of many large, unaligned image tiles that suffer from optical distortions. We developed the BigStitcher software that efficiently handles and reconstructs large multi-tile, multi-view acquisitions compensating all major optical effects, thereby making single-cell resolved whole-organ datasets amenable to biological studies.
Source:bioRxiv
Publisher:Cold Spring Harbor Laboratory (U.S.A.)
Article Number:343954
Date:10 June 2018
Official Publication:https://doi.org/10.1101/343954
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https://edoc.mdc-berlin.de/18360/Final version

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