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Fully Automated Registration of First-Pass Myocardial Perfusion MRI Using Independent Component Analysis

  • Conference paper
Information Processing in Medical Imaging (IPMI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4584))

Abstract

This paper presents a novel method for registration of cardiac perfusion MRI. The presented method successfully corrects for breathing motion without any manual interaction using Independent Component Analysis to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of ICA, and used to compute the displacement caused by breathing for each frame. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Validation experiments showed a reduction of the average LV motion from 1.26±0.87 to 0.64±0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65±7.89% to 0.87±3.88% between registered data and manual gold standard. We conclude that this fully automatic ICA-based method shows an excellent accuracy, robustness and computation speed, adequate for use in a clinical environment.

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Authors and Affiliations

  1. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands

    J. Milles, R. J. van der Geest, J. H. C. Reiber & B. P. F. Lelieveldt

  2. Advanced Imaging Research Center, Oregon Health & Science University, Portland, USA

    M. Jerosch-Herold

Authors
  1. J. Milles
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  2. R. J. van der Geest
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  3. M. Jerosch-Herold
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  4. J. H. C. Reiber
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  5. B. P. F. Lelieveldt
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Nico Karssemeijer Boudewijn Lelieveldt

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© 2007 Springer Berlin Heidelberg

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Milles, J., van der Geest, R.J., Jerosch-Herold, M., Reiber, J.H.C., Lelieveldt, B.P.F. (2007). Fully Automated Registration of First-Pass Myocardial Perfusion MRI Using Independent Component Analysis. In: Karssemeijer, N., Lelieveldt, B. (eds) Information Processing in Medical Imaging. IPMI 2007. Lecture Notes in Computer Science, vol 4584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73273-0_45

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  • DOI: https://doi.org/10.1007/978-3-540-73273-0_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73272-3

  • Online ISBN: 978-3-540-73273-0

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