Motion correction of magnetic resonance imaging data by using adaptive moving least squares method

Haewon Nam, Yeon Ju Lee, Byeongseon Jeong, Hae Jeong Park, Jungho Yoon

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Image artifacts caused by subject motion during the imaging sequence are one of the most common problems in magnetic resonance imaging (MRI) and often degrade the image quality. In this study, we develop a motion correction algorithm for the interleaved-MR acquisition. An advantage of the proposed method is that it does not require either additional equipment or redundant over-sampling. The general framework of this study is similar to that of Rohlfing et al. [1], except for the introduction of the following fundamental modification. The three-dimensional (3-D) scattered data approximation method is used to correct the artifacted data as a post-processing step. In order to obtain a better match to the local structures of the given image, we use the data-adapted moving least squares (MLS) method that can improve the performance of the classical method. Numerical results are provided to demonstrate the advantages of the proposed algorithm.

Original languageEnglish
Pages (from-to)659-670
Number of pages12
JournalMagnetic Resonance Imaging
Volume33
Issue number5
DOIs
StatePublished - Jun 2015

Keywords

  • 3-D image
  • Edge-directed interpolation
  • Gradients
  • Resampling

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