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International Conference on Functional Imaging and Modeling of the Heart

FIMH 2017: Functional Imaging and Modelling of the Heart pp 83–94Cite as

Using Atlas Prior with Graph Cut Methods for Right Ventricle Segmentation from Cardiac MRI

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10263))

Abstract

Right ventricle segmentation helps quantify many functional parameters of the heart and construct anatomical models for intervention planning. Here we propose a fast and accurate graph cut segmentation algorithm to extract the right ventricle from cine cardiac MRI sequences. A shape prior obtained by propagating the right ventricle label from an average atlas via affine registration is incorporated into the graph energy. The optimal segmentation obtained from the graph cut is iteratively refined to produce the final right ventricle blood pool segmentation. We evaluate our segmentation results against gold-standard expert manual segmentation of 16 cine MRI datasets available through the MICCAI 2012 Cardiac MR Right Ventricle Segmentation Challenge. Our method achieved an average Dice Index 0.83, a Jaccard Index 0.75, Mean absolute distance of 5.50 mm, and a Hausdorff distance of 10.00 mm.

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Notes

  1. 1.

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Author information

Authors and Affiliations

  1. Chester F. Carlson Center for Imaging Science, Rochester, USA

    Shusil Dangi & Cristian A. Linte

  2. Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, USA

    Cristian A. Linte

Authors
  1. Shusil Dangi
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  2. Cristian A. Linte
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Correspondence to Shusil Dangi .

Editor information

Editors and Affiliations

  1. University of Toronto, Toronto, Ontario, Canada

    Mihaela Pop

  2. University of Toronto , Toronto, Ontario, Canada

    Graham A Wright

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Dangi, S., Linte, C.A. (2017). Using Atlas Prior with Graph Cut Methods for Right Ventricle Segmentation from Cardiac MRI. In: Pop, M., Wright, G. (eds) Functional Imaging and Modelling of the Heart. FIMH 2017. Lecture Notes in Computer Science(), vol 10263. Springer, Cham. https://doi.org/10.1007/978-3-319-59448-4_9

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  • DOI: https://doi.org/10.1007/978-3-319-59448-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59447-7

  • Online ISBN: 978-3-319-59448-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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