Automatic quality assessment in structural brain magnetic resonance imaging

Bénédicte Mortamet, Matt A. Bernstein, Clifford R. Jack, Jeffrey L. Gunter, Chadwick Ward, Paula J. Britson, Reto Meuli, Jean Philippe Thiran, Gunnar Krueger

Research output: Contribution to journalArticlepeer-review

89 Scopus citations


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 T1-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.

Original languageEnglish (US)
Pages (from-to)365-372
Number of pages8
JournalMagnetic Resonance in Medicine
Issue number2
StatePublished - Aug 2009


  • Artifact detection
  • Automatic quality assessment
  • Image quality
  • Magnetic resonance imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


Dive into the research topics of 'Automatic quality assessment in structural brain magnetic resonance imaging'. Together they form a unique fingerprint.

Cite this