A scalable and modular automated pipeline for stitching of large electron microscopy datasets
- Allen Institute for Brain Science, United States
- Janelia Research Campus, United States
- Yikes LLC, United States
- Swedish Neuroscience Institute, United States
- St. Jude Children's Research Hospital, United States
Abstract
Serial-section electronmicroscopy (ssEM) is themethod of choice for studyingmacroscopic 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 called connectomes. In order to use this data, consisting of up to 108 individual 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 pipeline ASAP (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 the Render (27) services used in the volume assembly of the brain of adult Drosophilamelanogaster (30). It achieves high throughput by operating on themeta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP ismodular, 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 stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (28; 8) 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.
Data availability
The current manuscript describes is a software infrastructure resource that is being made publicly available. The manuscript is not a data generation manuscript. Nevertheless, one of the datasets used is already publicly available on https://www.microns-explorer.org/cortical-mm3#em-imagery with available imagery and segmentation (https://tinyurl.com/cortical-mm3).Moreover cloud-volume (https://github.com/seung-lab/cloud-volume) can be used to programmatically download EM imagery from either Amazon or Google with the cloud paths described below. The imagery was reconstructed in two portions, referred to internally by their nicknames 'minnie65' and 'minnie35' reflecting their relative portions of the total data. The two portions are aligned across an interruption in sectioning.minnie65:AWS Bucket: precomputed://https://bossdb-open-data.s3.amazonaws.com/iarpa_microns/minnie/minnie65/emGoogle Bucket: precomputed://https://storage.googleapis.com/iarpa_microns/minnie/minnie65/emminnie35:AWS Bucket: precomputed://https://bossdb-open-data.s3.amazonaws.com/iarpa_microns/minnie/minnie35/emGoogle Bucket: precomputed://https://storage.googleapis.com/iarpa_microns/minnie/minnie35/emWe have also made available in Dryad raw data of the remaining datasets https://doi.org/10.5061/dryad.qjq2bvqhr
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ASAP-TEM-sampleDryad Digital Repository, doi:10.5061/dryad.qjq2bvqhr.
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MICrONS multi-area datasethttps://doi.org/10.1101/2021.07.28.454025.
Article and author information
Author details
Nuno Macarico da Costa
Funding
IARPA (D16PC00004)
- Gayathri Mahalingam
- Russel Torres
- Daniel Kapner
- Tim Fliss
- Shamishtaa Seshamani
- Rob Young
- Samuel Kinn
- JoAnn Buchanan
- Marc M Takeno
- Wenjing Yin
- Daniel J Bumbarger
- R Clay Reid
- Forrest Collman
- Nuno Macarico da Costa
The funders had no role in study design and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Albert Cardona, University of Cambridge, United Kingdom
Ethics
Animal experimentation: All procedures were carried out in accordance with Institutional Animal Care and Use Committee approval at the Allen Institute for Brain Science with protocol numbers 1503, 1801 and 1808
Human subjects: Human surgical specimen was obtained from local hospital in collaboration with local neurosurgeon. The sample collection was approved by the Western Institutional Review Board (Protocol # SNI 0405). Patient provided informed consent and experimental procedures were approved by hospital institute review boards before commencing the study.
Version history
- Preprint posted: November 25, 2021 (view preprint)
- Received: December 20, 2021
- Accepted: July 10, 2022
- Accepted Manuscript published: July 26, 2022 (version 1)
- Version of Record published: August 30, 2022 (version 2)
Copyright
© 2022, Mahalingam et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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A scalable and modular automated pipeline for stitching of large electron microscopy datasets
eLife 11:e76534.
https://doi.org/10.7554/eLife.76534
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