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. 2019 Sep;16(9):870-874.
doi: 10.1038/s41592-019-0501-0. Epub 2019 Aug 5.

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

David Hörl #  1   2 , Fabio Rojas Rusak #  3 , Friedrich Preusser  2 , Paul Tillberg  4 , Nadine Randel  4 , Raghav K Chhetri  4 , Albert Cardona  4   5 , Philipp J Keller  4 , Hartmann Harz  1 , Heinrich Leonhardt  1 , Mathias Treier  3   6 , Stephan Preibisch  7
Affiliations

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

David Hörl et al. Nat Methods. 2019 Sep.

Abstract

Light-sheet imaging of cleared and expanded samples creates terabyte-sized datasets that consist of many unaligned three-dimensional image tiles, which must be reconstructed before analysis. We developed the BigStitcher software to address this challenge. BigStitcher enables interactive visualization, fast and precise alignment, spatially resolved quality estimation, real-time fusion and deconvolution of dual-illumination, multitile, multiview datasets. The software also compensates for optical effects, thereby improving accuracy and enabling subsequent biological analysis.

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