mri
mri standardizes diverse human brain atlases, provides transformation functions between atlas representations, and generates projectomes from functional MRI (fMRI) and diffusion tensor imaging (DTI) to support large-scale connectome analysis.
Key Features:
- Standardization of Brain Atlases: Consolidates a wide array of human brain atlases into a single, curated library for consistent atlas representation.
- Comprehensive Metadata and Protocols: Associates each atlas with metadata and standardized protocol specifications for orientation, resolution, labeling schemes, file storage formats, and coordinate space designations.
- Transformation Functions: Provides functions to convert between different atlas representations to enable integration of diverse datasets.
- Projectome Generation: Produces projectomes that map relationships between brain regions derived from fMRI and DTI for large-scale connectivity mapping.
Scientific Applications:
- Neuroscientific Inference: Enables more accurate and consistent localization of regions of interest across studies, improving the validity of statistical inferences.
- Connectome Analysis: Supports large-scale connectome analyses by providing standardized parcellations and projectomes for network and connectivity studies.
- Integration with Statistical Machine Learning: Provides standardized brain parcellations and derived summary data that facilitate the application and evaluation of statistical machine learning methods on neuroimaging data.
Methodology:
Processes raw imaging data from multiple labs and experiments through standardized protocols to produce summary statistics, quality assurance metrics, and final projectomes.
Topics
Details
- Tool Type:
- command-line tool, web application
- Added:
- 1/14/2020
- Last Updated:
- 1/14/2021
Operations
Publications
Lawrence RM, Bridgeford EW, Myers PE, Arvapalli GC, Ramachandran SC, Pisner DA, Frank PF, Lemmer AD, Nikolaidis A, Vogelstein JT. Standardizing Human Brain Parcellations. Unknown Journal. 2019. doi:10.1101/845065.
DOI: 10.1101/845065
Links
Repository
https://github.com/neurodata/neuroparc