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Automated segmentation of the injured kidney due to abdominal trauma

  • Image & Signal Processing
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

The objective of this study is to propose and validate a computer-aided segmentation system which performs the automated segmentation of injured kidney in the presence of contusion, peri-, intra-, sub-capsular hematoma, laceration, active extravasation and urine leak due to abdominal trauma. In the present study, total multi-phase CT scans of thirty-seven cases were used; seventeen of them for the development of the method and twenty of them for the validation of the method. The proposed algorithm contains three steps: determination of the kidney mask using Circular Hough Transform, segmentation of the renal parenchyma of the kidney applying the symmetry property to the histogram, and estimation of the kidney volume. The results of the proposed method were compared using various metrics. The kidney quantification led to 92.3 ± 4.2% Dice coefficient, 92.8 ± 7.4%/92.3 ± 5.1% precision/sensitivity, 1.4 ± 0.6 mm/2.0 ± 1.0 mm average surface distance/root-mean-squared error for intact and 87.3 ± 8.4% Dice coefficient, 84.3 ± 13.8%/92.2 ± 3.8% precision/sensitivity and 2.4 ± 2.2 mm/4.0 ± 4.2 mm average surface distance/root-mean-squared error for injured kidneys. The segmentation of the injured kidney was satisfactorily performed in all cases. This method may lead to the automated detection of renal lesions due to abdominal trauma and estimate the intraperitoneal blood amount, which is vital for trauma patients.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Istanbul Arel University, Istanbul, Turkey

    Gokalp Tulum & Onur Osman

  2. Department of Radiology, Sparrow Health System, Lansing, MI, USA

    Uygar Teomete

  3. Department of Radiology, Gulhane Research and Training Hospital, Ankara, Turkey

    Ferhat Cuce & Tuncer Ergin

  4. Department of Radiology, Ankara Numune Training and Research Hospital, Ankara, Turkey

    Murathan Koksal

  5. Department of General Surgery, Akdeniz University, Antalya, Turkey

    Ozgur Dandin

Authors
  1. Gokalp Tulum
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  2. Uygar Teomete
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  3. Ferhat Cuce
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  4. Tuncer Ergin
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  5. Murathan Koksal
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  6. Ozgur Dandin
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  7. Onur Osman
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Correspondence to Gokalp Tulum.

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The authors declare that they have no conflicts of interest. No funding was received for this study.

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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.

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This article is part of the Topical Collection on Image & Signal Processing

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Tulum, G., Teomete, U., Cuce, F. et al. Automated segmentation of the injured kidney due to abdominal trauma. J Med Syst 44, 5 (2020). https://doi.org/10.1007/s10916-019-1476-1

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  • DOI: https://doi.org/10.1007/s10916-019-1476-1

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