Automatic quality assessment in structural brain magnetic resonance imaging

Details

Ressource 1Download: BIB_E2D6F74284E1.P001.pdf (1212.16 [Ko])
State: Public
Version: author
Serval ID
serval:BIB_E2D6F74284E1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Automatic quality assessment in structural brain magnetic resonance imaging
Journal
Magnetic Resonance in Medicine
Author(s)
Mortamet B., Bernstein M. A., Jack C. R. Jr. , Gunter J. L., Ward C., Britson P. J., Meuli R., Thiran J. P., Krueger G.
ISSN
1522-2594
Publication state
Published
Issued date
2009
Peer-reviewed
Oui
Volume
62
Number
2
Pages
365-372
Language
english
Abstract
MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.
Pubmed
Web of science
Create date
25/08/2009 9:45
Last modification date
20/08/2019 16:06
Usage data