Automatic motion correction of clinical shoulder MR images

Armando Manduca, Kiaran P. McGee, E. Brian Welch, Joel P. Felmlee, Richard L. Ehman

Research output: Contribution to journalConference articlepeer-review


A technique for the automatic correction of motion artifacts in MR images was developed. The algorithm uses only the raw (complex) data from the MR scanner, and requires no knowledge of the patient motion during the acquisition. It operates by searching over the space of possible patient motions and determining the motion which, when used to correct the image, optimizes the image quality. The performance of this algorithm was tested in coronal images of the rotator cuff in a series of 144 patients. A four observer comparison of the autocorrected images with the uncorrected images demonstrated that motion artifacts were significantly reduced in 48% of the cases. The improvements in image quality were similar to those achieved with a previously reported navigator echo-based adaptive motion correction. The results demonstrate that autocorrection is a practical technique for retrospectively reducing motion artifacts in a demanding clinical MRI application. It achieves performance comparable to a navigator based correction technique, which is significant because autocorrection does not require an imaging sequence that has been modified to explicitly track motion during acquisition. The approach is flexible and should be readily extensible to other types of MR acquisitions that are corrupted by global motion.

Original languageEnglish (US)
Pages (from-to)367-374
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Issue numberI
StatePublished - Jan 1 1999
EventProceedings of the 1999 Medical Imaging - Image Processing - San Diego, CA, USA
Duration: Feb 22 1999Feb 25 1999

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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