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Spleen Segmentation and Assessment in CT Images for Traumatic Abdominal Injuries

  • Systems-Level Quality Improvement
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Abstract

Spleen segmentation is especially challenging as the majority of solid organs in the abdomen region have similar gray level range. Physician analysis of computed tomography (CT) images to assess abdominal trauma could be very time consuming and hence, automating this process can reduce time to treatment. The proposed method presented in this paper is a fully automated and knowledge based technique that employs anatomical information to accurately segment the spleen in CT images. The spleen detection procedure is proposed to locate the spleen in both healthy and injured cases. In the presence of hemorrhage and laceration, the edge merging technique is used. The accuracy of the method is measured by some criteria such as mis–segmented area, accuracy, specificity and sensitivity. The results show that the proposed spleen segmentation method performs well and outperforms other methods.

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Acknowledgments

The authors would like to thank Dr. Ashwin Belle for his valuable comments and Virginia Commonwealth University Medical Center for providing data for the study.

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Authors and Affiliations

  1. Emergency Medicine Department, University of Michigan, Ann Arbor, MI, USA

    S. M. Reza Soroushmehr, Somayeh Molaei, Kevin Ward & Kayvan Najarian

  2. Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA, USA

    Pavani Davuluri & Rosalyn Hobson Hargraves

  3. Department of Radiology, Virginia Commonwealth University, Richmond, VA, USA

    Yang Tang & Charles H. Cockrell

  4. Department of Computational Medicine and Bioinformatics, University of Michigan Center for Integrative Research in Critical Care (MCIRCC), Ann Arbor, MI, USA

    S. M. Reza Soroushmehr, Kevin Ward & Kayvan Najarian

Authors
  1. S. M. Reza Soroushmehr
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  2. Pavani Davuluri
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  3. Somayeh Molaei
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  4. Rosalyn Hobson Hargraves
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  5. Yang Tang
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  6. Charles H. Cockrell
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  7. Kevin Ward
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  8. Kayvan Najarian
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Corresponding author

Correspondence to S. M. Reza Soroushmehr.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Reza Soroushmehr, S.M., Davuluri, P., Molaei, S. et al. Spleen Segmentation and Assessment in CT Images for Traumatic Abdominal Injuries. J Med Syst 39, 87 (2015). https://doi.org/10.1007/s10916-015-0271-x

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  • DOI: https://doi.org/10.1007/s10916-015-0271-x

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