Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets.

ABSTRACT:

Background

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. Unfortunately, many neuroscience laboratories lack the computational resources to work with datasets of this size: computer vision tools are often not portable or scalable, and there is considerable difficulty in reproducing results or extending methods.

Results

We developed an ecosystem of neuroimaging data analysis pipelines that use open-source

SUBMITTER: Johnson EC 

PROVIDER: S-EPMC7751400 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature