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Fully automated MR liver volumetry using watershed segmentation coupled with active contouring

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction.

Methods

The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An active contour model was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the “gold standard” references which were estimated by an expert abdominal radiologist.

Results

The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the “gold standard” manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average.

Conclusions

We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists’ time for manual liver volumetry of 24.7 min per case.

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Acknowledgements

This research is funded by the Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.01-2013.47.

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Authors and Affiliations

  1. Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Hieu Trung Huynh & Ngoc Le-Trong

  2. Faculty of Information Technology, University of Science, Ho Chi Minh City, Vietnam

    Ngoc Le-Trong & Pham The Bao

  3. Faculty of Mathematics and Computer Science, University of Science, Ho Chi Minh City, Vietnam

    Pham The Bao

  4. Department of Radiology, The University of Chicago, Chicago, IL, 60637, USA

    Aytek Oto

  5. Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL, 60616, USA

    Kenji Suzuki

Authors
  1. Hieu Trung Huynh
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  2. Ngoc Le-Trong
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  3. Pham The Bao
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  4. Aytek Oto
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  5. Kenji Suzuki
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Corresponding author

Correspondence to Hieu Trung Huynh.

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Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the study.

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Huynh, H.T., Le-Trong, N., Bao, P.T. et al. Fully automated MR liver volumetry using watershed segmentation coupled with active contouring. Int J CARS 12, 235–243 (2017). https://doi.org/10.1007/s11548-016-1498-9

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  • DOI: https://doi.org/10.1007/s11548-016-1498-9

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