MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites

Quality control of MRI is essential for excluding problematic acquisitions and avoiding bias in subsequent image processing and analysis. Visual inspection is subjective and impractical for large scale datasets. Although automated quality assessments have been demonstrated on single-site datasets, i...

Full description

Saved in:

Bibliographic Details
Published in:	PloS one Vol. 12; no. 9; p. e0184661
Main Authors:	Esteban, Oscar, Birman, Daniel, Schaer, Marie, Koyejo, Oluwasanmi O., Poldrack, Russell A., Gorgolewski, Krzysztof J.
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 25.09.2017 Public Library of Science (PLoS)
Subjects:	Artificial intelligence Autism Automation Biology and Life Sciences Brain - diagnostic imaging Brain research Classifiers Computer and Information Sciences Computer science Data acquisition Datasets Engineering and Technology Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Image quality Information processing Inspection Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Medicine and Health Sciences Methods Neuroimaging Neuroimaging - methods Neurology NMR Noise Nuclear magnetic resonance Observer Variation Quality assessment Quality control Research and Analysis Methods Social Sciences Software Statistical analysis Statistical methods Visual perception United States United States > US California
ISSN:	1932-6203, 1932-6203
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!