SABER: Scalable Analytics for Brain Exploration Research

Presenter: Erik Johnson, Daniel Xenes, William R. Gray Roncal, Johns Hopkins University APL

Session 1 (Americas-EMEA) Monday, February 8th 15:50 UTC

Summary: “Emerging neuroimaging datasets (collected with imaging techniques such as electron microscopy, optical microscopy, or X-ray microtomography) describe the location and properties of neurons and their connections at unprecedented scale, promising new ways of understanding the brain. These modern imaging techniques used to interrogate the brain can quickly accumulate gigabytes to petabytes of structural brain imaging data. We developed an ecosystem of neuroimaging data analysis pipelines that use open-source algorithms and the Common Workflow Language to create standardized modules and end-to-end optimized approaches. As exemplars we apply our tools to estimate synapse-level connectomes from electron microscopy data and cell distributions from X-ray microtomography data. To facilitate scientific discovery, we propose a generalized processing framework, which connects and extends existing open-source projects to provide large-scale data storage, reproducible algorithms, and workflow execution engines.”

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