Name
Title | ||
|---|---|---|
Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability |
Abstract | ||
|---|---|---|
Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.3389/fninf.2022.828458 | FRONTIERS IN NEUROINFORMATICS |
Keywords | DocType | Volume |
connectome, annotation, software, standard, queries, reproducibility | Journal | 16 |
ISSN | Citations | PageRank |
1662-5196 | 0 | 0.34 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Morgan Sanchez | 1 | 0 | 0.34 |
| Dymon Moore | 2 | 0 | 0.34 |
| Erik C. Johnson | 3 | 0 | 1.35 |
| Brock Wester | 4 | 0 | 0.34 |
| Jeff W. Lichtman | 5 | 134 | 12.41 |
| William Gray-Roncal | 6 | 0 | 0.34 |