• DocumentCode
    1483810
  • Title

    Exploiting Quasiperiodicity in Motion Correction of Free-Breathing Myocardial Perfusion MRI

  • Author

    Wollny, Gert ; Ledesma-Carbayo, Maria J. ; Kellman, Peter ; Santos, Andres

  • Author_Institution
    Dept. of Electron. Eng., Univ. Politech. de Madrid, Madrid, Spain
  • Volume
    29
  • Issue
    8
  • fYear
    2010
  • Firstpage
    1516
  • Lastpage
    1527
  • Abstract
    Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose an automatic registration scheme that exploits the quasiperiodicity of free breathing to decouple movement from intensity change. First, we identify and register a subset of the images corresponding to the same phase of the breathing cycle. This registration step deals with small differences caused by movement but maintains the full range of intensity change. The remaining images are then registered to synthetic references that are created as a linear combination of images belonging to the already registered subset. Because of the quasiperiodic respiratory movement, the subset images are distributed evenly over time and, therefore, the synthetic references exhibit intensities similar to their corresponding unregistered images. Thus, this second registration step needs to account only for the movement. Validation experiments were performed on data obtained from six patients, three slices per patient, and the automatically obtained perfusion profiles were compared with profiles obtained by manually segmenting the myocardium. The results show that our automatic approach is well suited to compensate for the free-breathing movement and that it achieves a significant improvement in the average Pearson correlation coefficient between manually and automatically obtained perfusion profiles before ( 0.87 ±0.18) and after (0.96 ±0.09) registration.
  • Keywords
    biomedical MRI; cardiology; image registration; image segmentation; medical image processing; motion compensation; pneumodynamics; MRI; automatic registration; average Pearson correlation coefficient; free-breathing; gadolinium-enhanced magnetic resonance imaging; image acquisition; motion correction; myocardial perfusion MRI; quasiperiodicity; respiratory movement; Biomedical engineering; Biomedical imaging; Blood; Heart; Image analysis; Image segmentation; Magnetic analysis; Magnetic resonance imaging; Myocardium; Tracking; Heart; image registration; myocardial perfusion; Algorithms; Gadolinium; Heart; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Movement; Myocardial Perfusion Imaging; Pattern Recognition, Automated; Reproducibility of Results; Respiration;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2010.2049270
  • Filename
    5458069