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Automated quality control of brain MR images by Elias L. Gedamu; D.L. Collins; Douglas L. Arnold is a Medicine article available to read on EtoBox.

What is Automated quality control of brain MR images about?

## Abstract ## Purpose To present a novel fully automated method for assessing the quality of magnetic resonance imaging (MRI) data acquired in a clinical trials environment. ## Materials and Methods This work was performed in the context of clinical trials for multiple sclerosis. Quality control (QC) procedures included were: (i) patient brain identity verification, (ii) alphanumeric parameter matching, (iii) signal‐to‐noise ratio estimation, (iv) gadolinium‐enhancement verification, and (v) detection of ghosting due to head motion. Each QC procedure produces a quantitative measurement which is compared against an acceptance threshold that was determined based on receiver operating characteristic analysis of traditional manual and visual QC performed by trained experts. ## Results The automated QC results have high sensitivity and specificity when compared with the visual QC. ## Conclusion Our automated objective QC procedure can replace many manual subjective procedures to provide increased data throughput while reducing reader variability. J. Magn. Reson. Imaging 2008;28:308–319. © 2008 Wiley‐Liss, Inc.

Who reads Automated quality control of brain MR images?

Author

Elias L. Gedamu; D.L. Collins; Douglas L. Arnold

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 1053-1807)

Published

2008

Language

EN

Field

Medicine (Health Sciences)