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Proceedings Paper

Automatic motion correction of clinical shoulder MR images
Author(s): Armando Manduca; Kiaran P. McGee; Edward B. Welch; Joel P. Felmlee; Richard L. Ehman
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Paper Abstract

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 autocorrelated 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 autocorrelation 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.

Paper Details

Date Published: 21 May 1999
PDF: 8 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348591
Show Author Affiliations
Armando Manduca, Mayo Clinic and Foundation (United States)
Kiaran P. McGee, Mayo Clinic and Foundation (United States)
Edward B. Welch, Mayo Clinic and Foundation (United States)
Joel P. Felmlee, Mayo Clinic and Foundation (United States)
Richard L. Ehman, Mayo Clinic and Foundation (United States)


Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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