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http://www.chibi.ubc.ca/WhiteText/
Freely available corpus of manually annotated brain region mentions created to facilitate text mining of neuroscience literature. The corpus contains 1,377 abstracts with 18,242 brain region annotations. Interannotator agreement was evaluated for a subset of the documents, and was 90.7% and 96.7% for strict and lenient matching respectively. We observed a large vocabulary of over 6,000 unique brain region terms and 17,000 words. For automatic extraction of brain region mentions we evaluated simple dictionary methods and complex natural language processing techniques. The dictionary methods based on neuroanatomical lexicons recalled 36% of the mentions with 57% precision. The best performance was achieved using a conditional random field (CRF) with a rich feature set. Features were based on morphological, lexical, syntactic and contextual information. The CRF recalled 76% of mentions at 81% precision, by counting partial matches recall and precision increase to 86% and 92% respectively. We suspect a large amount of error is due to coordinating conjunctions, previously unseen words and brain regions of less commonly studied organisms. We found context windows, lemmatization and abbreviation expansion to be the most informative techniques. We encourage you to test new methods and applications of the dataset. Please contact us if you do, we would like to hear about and link to your work. The abstracts are from PubMed/Medline, specifically The Journal of Comparative Neurology.
Proper citation: Automated recognition of brain region mentions in neuroscience literature. (RRID:SCR_002731) Copy
http://www.nitrc.org/projects/minctoolkittest/
Sample data in MINC format and collection of scripts to verify correct installation of minc-toolkit.
Proper citation: minc-toolkit-testsuite (RRID:SCR_014139) Copy
http://www.nitrc.org/projects/parktdi/
A project which contains data and analysis pipelines for a set of 53 subjects in a cross-sectional Parkinsons disease (PD) study. The dataset contains diffusion-weighted images (DWI) of 27 PD patients and 26 age, sex, and education-matched control subjects. The DWIs were acquired with 120 unique gradient directions, b=1000 and b=2500 s/mm2, and isotropic 2.4 mm3 voxels. The acquisition used a twice-refocused spin echo sequence in order to avoid distortions induced by eddy currents.
Proper citation: High-quality diffusion-weighted imaging of Parkinsons disease (RRID:SCR_014121) Copy
http://www.nitrc.org/projects/elude
A longitudinal study of late-life depression at Duke University. There are 281 depressed subjects and 154 controls included. An MR scan of each subject was obtained every 2 years for up to 8 years (total of 1093 scans). Clinical assessments occurred more frequently and consists of a battery of psychiatric tests, including several depression-specific tests.
Proper citation: Efficient Longitudinal Upload of Depression in the Elderly (ELUDE) (RRID:SCR_014103) Copy
http://www.nitrc.org/projects/sct
A comprehensive and open-source library of analysis tools for multi-parametric MRI of the spinal cord. The toolbox includes a template and several atlases, along with state-of-the-art methods to register any data to the template. It also includes useful scripts for data preprocessing: extraction of centerline, automatic segmentation, slice-wise motion correction, etc.
Proper citation: Spinal Cord Toolbox (RRID:SCR_014170) Copy
https://hub.docker.com/r/kaczmarj/neurodocker/
Software tool to generate Dockerfiles and Singularity recipes for neuroimaging with simple command-line interface. Command line program that generates custom Dockerfiles and Singularity recipes for neuroimaging and minifies existing containers. Supports AFNI, ANTs, Convert3D, Dcm2niix, FreeSurfer, FSL, Matlab Compiler Runtime, MINC, Miniconda, MRtrix3, NeuroDebian, PETPVC, and SPM12.
Proper citation: Neurodocker (RRID:SCR_017426) Copy
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