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Automatic Perfusion Analysis Using Phase-Based Registration and Object-Based Image Analysis

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Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges (STACOM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8896))

Abstract

MRI perfusion imaging enables the non-invasive assessment of myocardial blood supply. The purpose of the presented work is to enable a quantitative assessment of the image sequences for clinical application. To this end an automatic preprocessing including ROI detection and outlier removal has been combined with a phase-based registration approach and an object-based myocardium segmentation. The suggested processing pipeline has been tested with 21 image sequences provided by the STACOM motion correction challenge. The corrected image sequences have been assessed by comparison with gamma variate curves fitted to the voxels intensity curves. The automatic segmentation could be compared with expert segmentations provided by the challenge organizers. The results indicate an improvement through the motion correction and a good agreement with the reference segmentation in most cases.

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Authors and Affiliations

  1. Fraunhofer MEVIS, Bremen, Germany

    Lennart Tautz, Teodora Chitiboi & Anja Hennemuth

Authors
  1. Lennart Tautz
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  2. Teodora Chitiboi
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  3. Anja Hennemuth
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Corresponding author

Correspondence to Lennart Tautz .

Editor information

Editors and Affiliations

  1. University Pompeu Fabra, Barcelona, Spain

    Oscar Camara

  2. Siemens Corporate Technology, Princeton, New Jersey, USA

    Tommaso Mansi

  3. Sunnybrook Research Institute, Toronto, Ontario, Canada

    Mihaela Pop

  4. St. Thomas Hospital, London, United Kingdom

    Kawal Rhode

  5. Inria, Sophia Antipolis, France

    Maxime Sermesant

  6. University of Auckland, Auckland, New Zealand

    Alistair Young

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© 2015 Springer International Publishing Switzerland

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Tautz, L., Chitiboi, T., Hennemuth, A. (2015). Automatic Perfusion Analysis Using Phase-Based Registration and Object-Based Image Analysis. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges. STACOM 2014. Lecture Notes in Computer Science(), vol 8896. Springer, Cham. https://doi.org/10.1007/978-3-319-14678-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-14678-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14677-5

  • Online ISBN: 978-3-319-14678-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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