BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples
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 visualizatio...
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Veröffentlicht in: | Nature methods 2019-09, Vol.16 (9), p.870-874 |
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Hauptverfasser: | , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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.
BigStitcher enables fast and accurate alignment and reconstruction of terabyte-sized imaging datasets of cleared and expanded samples. |
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ISSN: | 1548-7091 1548-7105 |
DOI: | 10.1038/s41592-019-0501-0 |