Autofocusing of clinical shoulder MR images for correction of motion artifacts

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

A post-processing’’autofocusing” algorithm for the reduction of motion artifacts in MR images has been developed and tested on a large clinical data set of high resolution shoulder images. The algorithm uses only the raw (complex) data from the MR scanner, and requires no knowledge of the patient motion during the scan, deducing that from the raw data itself. It operates by searching over the space of possible patient motions and optimizing the image quality. Evaluation of this technique on the clinical data set (for which navigator echo based measured motions and corrected images were available) show that the algorithm can correct for the effects of global translation during the scan almost as well as the navigator echo approach and is more robust.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention ─ MICCAI 1998 - 1st International Conference, Proceedings
EditorsWilliam M. Wells, Alan Colchester, Scott Delp
PublisherSpringer Verlag
Pages598-605
Number of pages8
ISBN (Print)3540651365, 9783540651369
DOIs
StatePublished - 1998
Event1st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 1998 - Cambridge, United States
Duration: Oct 11 1998Oct 13 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1496
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 1998
Country/TerritoryUnited States
CityCambridge
Period10/11/9810/13/98

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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