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A scalable and modular automated pipeline for stitching of large electron microscopy datasets

Authors :
Sharmishtaa Seshamani
Sam Kinn
Clay Reid
Julie Nyhus
Wenjing Yin
Eric T. Trautman
Stephan Saalfeld
JoAnn Buchanan
Stephen J. Smith
Khaled Khairy
R. P. Gwinn
Russel Torres
Tim P. Fliss
N. Macarico da Costa
Daniel J. Bumbarger
Gayathri Mahalingam
Marc Takeno
Ed S. Lein
Daniel Kapner
R.D. Young
Forrest Collman
Eric Perlman
Source :
eLife. 11
Publication Year :
2022
Publisher :
eLife Sciences Publications, Ltd, 2022.

Abstract

Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so calledconnectomes. In order to use this data, consisting of up to 108individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipelineASAP(Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of theRender[18] services used in the volume assembly of the brain of adultDrosophila melanogaster[2]. It achieves high throughput by operating on the meta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP is modular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous processing of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex [1, 25] at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

Details

ISSN :
2050084X
Volume :
11
Database :
OpenAIRE
Journal :
eLife
Accession number :
edsair.doi.dedup.....fc5d61fded7bab2966dc3c43f231c353