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Semi-automated Processing of Real-Time CMR Scans for Left Ventricle Segmentation

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Biomedical Image Registration (WBIR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10883))

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Abstract

We present a workflow for processing real-time cardiac MR (RT-CMR) scans for segmenting the left ventricle (LV) on short-axis slices (SAX). Our method is based on image registration, where the LV endocardium and epicardium are segmented by propagating a reference contour over all the frames of the RT-CMR SAX scans. Our method was evaluated on 19 subjects, the accuracy of the automatic LV endocardium and epicardium segmentation was compared to those defined manually. The proposed method obtained a dice similarity coefficient (DSC) of 0.94 and a mean surface-to-surface distance (MSD) measure of 0.89 ± 0.53 mm. Additionally, a number of automatically obtained clinical measures were compared to ground truth values. On average we obtained a Pearson’s correlation coefficient (R) of 0.94 (0.99–0.74).

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Author information

Authors and Affiliations

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

    Rahil Shahzad, Boudewijn P. F. Lelieveldt & Rob van der Geest

  2. Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany

    Martin Fasshauer & Joachim Lotz

  3. Intelligent Systems Department, Delft University of Technology, Delft, The Netherlands

    Boudewijn P. F. Lelieveldt

Authors
  1. Rahil Shahzad
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  2. Martin Fasshauer
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  3. Boudewijn P. F. Lelieveldt
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  4. Joachim Lotz
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  5. Rob van der Geest
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Corresponding author

Correspondence to Rahil Shahzad .

Editor information

Editors and Affiliations

  1. Erasmus MC, Rotterdam, The Netherlands

    Stefan Klein

  2. Leiden University Medical Center, Leiden, The Netherlands

    Marius Staring

  3. Inria/ICM ARAMIS Lab, Paris, France

    Stanley Durrleman

  4. University of Copenhagen, Copenhagen, Denmark

    Stefan Sommer

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Shahzad, R., Fasshauer, M., Lelieveldt, B.P.F., Lotz, J., van der Geest, R. (2018). Semi-automated Processing of Real-Time CMR Scans for Left Ventricle Segmentation. In: Klein, S., Staring, M., Durrleman, S., Sommer, S. (eds) Biomedical Image Registration. WBIR 2018. Lecture Notes in Computer Science(), vol 10883. Springer, Cham. https://doi.org/10.1007/978-3-319-92258-4_6

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  • DOI: https://doi.org/10.1007/978-3-319-92258-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92257-7

  • Online ISBN: 978-3-319-92258-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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