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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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References

  1. Manning, W.J., Pennell, D.J.: Cardiovascular Magnetic Resonance. Elsevier Health Sciences, Philadelphia (2010)

    Google Scholar 

  2. Zhang, S., Uecker, M., Voit, D., Merboldt, K.D., Frahm, J.: Real-time cardiovascular magnetic resonance at high temporal resolution: radial FLASH with nonlinear inverse reconstruction. J. Cardiovas. Magn. Reson. 12(1), 39 (2010)

    Article  Google Scholar 

  3. Uecker, M., Zhang, S., Voit, D., Karaus, A., Merboldt, K.D., Frahm, J.: Real-time MRI at a resolution of 20 ms. NMR in Biomed. 23(8), 986–994 (2010)

    Article  Google Scholar 

  4. Sotiras, A., Davatzikos, C., Paragios, N.: Deformable medical image registration: a survey. IEEE Trans. Med. Imaging 32(7), 1153–1190 (2013)

    Article  Google Scholar 

  5. Metz, C., Klein, S., Schaap, M., van Walsum, T., Niessen, W.J.: Nonrigid registration of dynamic medical imaging data using nD+t B-splines and a groupwise optimization approach. Med. Image Anal. 15(2), 238–249 (2011)

    Article  Google Scholar 

  6. Klein, S., Staring, M., Murphy, K., Viergever, M.A., Pluim, J.P.: Elastix: a toolbox for intensity-based medical image registration. IEEE Trans. Med. Imaging 29(1), 196–205 (2010)

    Article  Google Scholar 

  7. Shahzad, R., Tao, Q., Dzyubachyk, O., Staring, M., Lelieveldt, B.P., van der Geest, R.J.: Fully-automatic left ventricular segmentation from long-axis cardiac cine MR scans. Med. Image Anal. 39, 44–55 (2017)

    Article  Google Scholar 

  8. Klein, S., Pluim, J.P., Staring, M., Viergever, M.A.: Adaptive stochastic gradient descent optimisation for image registration. Int. J. Comput. Vis. 81(3), 227 (2009)

    Article  Google Scholar 

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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 .

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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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