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Spleen Segmentation and Assessment in CT Images for Traumatic Abdominal Injuries.

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 treat...

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Published in:Journal of Medical Systems Vol. 39; no. 9; pp. 1 - 12
Main Authors: Reza Soroushmehr, S., Davuluri, Pavani, Molaei, Somayeh, Hargraves, Rosalyn, Tang, Yang, Cockrell, Charles, Ward, Kevin, Najarian, Kayvan
Format: diagnostic images equations & formulas research tables/charts Journal Article
Published: Springer Nature Sep2015
Online Access:View this record in EBSCOhost
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      dt: Sep2015
      vid: 39
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      pub: Springer Nature
      place: New York, New York
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        atl: Spleen Segmentation and Assessment in CT Images for Traumatic Abdominal Injuries.
      aug:
        au:
          Reza Soroushmehr, S.
          Davuluri, Pavani
          Molaei, Somayeh
          Hargraves, Rosalyn
          Tang, Yang
          Cockrell, Charles
          Ward, Kevin
          Najarian, Kayvan
        affil: Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond USA
      sug:
        subj:
          Spleen
          Tomography, X-Ray Computed
          Image Processing, Computer Assisted
          Abdominal Injuries
          Human
          Trauma
          Algorithms
      ab: 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.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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