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V0.1.1
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"description": "Runs ICA-FIX denoising on functional data preprocessed according to the HCP Minimal Preprocessing Pipeline. This Gear is based on scripts from the v4.0-alpha release of the ICAFIX, PostFix, and RestingStateStats pipelines.", | ||
"author": "Human Connectome Project", | ||
"maintainer": "Flywheel <[email protected]>", | ||
"license": "Apache-2.0", | ||
"license": "Other", | ||
"url": "https://github.com/Washington-University/Pipelines", | ||
"source": "https://github.com/flywheel-apps/hcp-icafix", | ||
"cite": "(1) G. Salimi-Khorshidi, G. Douaud, C.F. Beckmann, M.F. Glasser, L. Griffanti S.M. Smith. Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers. NeuroImage, 90:449-68, 2014 (2) L. Griffanti, G. Salimi-Khorshidi, C.F. Beckmann, E.J. Auerbach, G. Douaud, C.E. Sexton, E. Zsoldos, K. Ebmeier, N. Filippini, C.E. Mackay, S. Moeller, J.G. Xu, E. Yacoub, G. Baselli, K. Ugurbil, K.L. Miller, and S.M. Smith. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging. NeuroImage, 95:232-47, 2014", | ||
"version": "0.1.0", | ||
"version": "0.1.1", | ||
"custom": { | ||
"docker-image": "flywheel/hcp-icafix:0.1.0" | ||
"docker-image": "flywheel/hcp-icafix:0.1.1" | ||
}, | ||
"flywheel": { | ||
"suite": "Human Connectome Project" | ||
}, | ||
"config": { | ||
"FIXClassifier": { | ||
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