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

Hoerl, David; Rusak, Fabio Rojas; Preusser, Friedrich; Tillberg, Paul; Randel, Nadine; Chhetri, Raghav K.; Cardona, Albert; Keller, Philipp J.; Harz, Hartmann; Leonhardt, Heinrich; Treier, Mathias und Preibisch, Stephan (2019): BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples. In: Nature Methods, Bd. 16, Nr. 9

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.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Biologie > Department Biologie II
• Themengebiete: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie
• ISSN: 1548-7091
• Sprache: Englisch