Automatic quality assessment in structural brain magnetic resonance imaging.
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.
Mortamet
Bénédicte
B
Advanced Clinical Imaging Technology, Siemens Suisse SA, Healthcare Sector IM&WS-Centre d'Imagerie Biomédicale (CIBM), Lausanne, Switzerland. benedicte.mortamet@epfl.ch
Bernstein
Matt A
MA
Jack
Clifford R
CR
Gunter
Jeffrey L
JL
Ward
Chadwick
C
Britson
Paula J
PJ
Meuli
Reto
R
Thiran
Jean-Philippe
JP
Krueger
Gunnar
G
D000368:Aged; D000544:Alzheimer Disease / Q000473:pathology; D001921:Brain / Q000473:pathology*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000592:standards*; D008279:Magnetic Resonance Imaging / Q000592:standards*; D008297:Male; D011785:Quality Assurance, Health Care / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity