The LONI QC System: A Semi-Automated, Web-Based and Freely-Available Environment for the Comprehensive Quality Control of Neuroimaging Data

The LONI QC System: A Semi-Automated, Web-Based and Freely-Available Environment for the Comprehensive Quality Control of Neuroimaging Data

Quantifying, controlling, and monitoring image quality is an essential prerequisite for ensuring the validity and reproducibility of many types of neuroimaging data analyses. Implementation of quality control (QC) procedures is the key to ensuring that neuroimaging data are of high-quality and their...

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Bibliographic Details
Main Authors: Hosung Kim, Andrei Irimia, Samuel M. Hobel, Mher Pogosyan, Haoteng Tang, Petros Petrosyan, Rita Esquivel Castelo Blanco, Ben A. Duffy, Lu Zhao, Karen L. Crawford, Sook-Lei Liew, Kristi Clark, Meng Law, Pratik Mukherjee, Geoffrey T. Manley, John D. Van Horn, Arthur W. Toga
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-08-01
Series:Frontiers in Neuroinformatics
Subjects:
quality control
magnetic resonance imaging
diffusion tensor imaging
functional magnetic resonance imaging
LONI Pipeline
Online Access:https://www.frontiersin.org/article/10.3389/fninf.2019.00060/full

Internet

https://www.frontiersin.org/article/10.3389/fninf.2019.00060/full

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