EM and XRM Connectomics Imaging and Experimental Metadata Standards
arxiv(2024)
摘要
High resolution volumetric neuroimaging datasets from electron microscopy
(EM) and x-ray micro and holographic-nano tomography (XRM/XHN) are being
generated at an increasing rate and by a growing number of research teams.
These datasets are derived from an increasing number of species, in an
increasing number of brain regions, and with an increasing number of
techniques. Each of these large-scale datasets, often surpassing petascale
levels, is typically accompanied by a unique and varied set of metadata. These
datasets can be used to derive connectomes, or neuron-synapse level
connectivity diagrams, to investigate the fundamental organization of neural
circuitry, neuronal development, and neurodegenerative disease. Standardization
is essential to facilitate comparative connectomics analysis and enhance data
utilization. Although the neuroinformatics community has successfully
established and adopted data standards for many modalities, this effort has not
yet encompassed EM and XRM/ XHN connectomics data. This lack of standardization
isolates these datasets, hindering their integration and comparison with other
research performed in the field. Towards this end, our team formed a working
group consisting of community stakeholders to develop Image and Experimental
Metadata Standards for EM and XRM/XHN data to ensure the scientific impact and
further motivate the generation and sharing of these data. This document
addresses version 1.1 of these standards, aiming to support metadata services
and future software designs for community collaboration. Standards for derived
annotations are described in a companion document. Standards definitions are
available on a community github page. We hope these standards will enable
comparative analysis, improve interoperability between connectomics software
tools, and continue to be refined and improved by the neuroinformatics
community.
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