Automated segmentation of the skeleton in whole-body bone scans: Influence of difference in atlas

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Abstract

AIM: Automated segmentation of the skeleton is the first step for quantitative analysis and computer-aided diagnosis (CAD) of whole-body bone scans. The purpose of this study was to examine the influence of differences in skeletal atlas on the automated segmentation of skeletons in a Japanese patient group. METHODS: The study was based on a bone scan CAD system that included a skeletal atlas obtained using 10 normal bone scans from European patients and 23 normal bone scans from Japanese patients. These were incorporated into the CAD system. The performance of the skeletal segmentation, based on either the European or the Japanese Atlas, was evaluated independently by three observers in a group of 50 randomly selected bone scans from Japanese patients. RESULTS: The skeletal segmentation was classified as correct in 41-44 of the 50 cases by the three observers using the Japanese atlas. The corresponding results were 15-18 of the 50 cases using the European atlas, and this difference was statistically significant (P<0.001). The anatomical areas most commonly classified as not correct were the skull, cervical vertebrae, and ribs. CONCLUSION: Automated segmentation of the skeleton in a Japanese patient group was more successful when the CAD system based on a Japanese atlas was used than when the corresponding system based on a European atlas was used. The results of this study indicate that it is of value to use a skeletal atlas based on normal Japanese bone scans in a CAD system for Japanese patients. © 2012 Wolters Kluwer Health | Lippincott Williams &Wilkins.

Journal

  • Nuclear Medicine Communications

    Nuclear Medicine Communications 33(9), 947-953, 2012-09-01

    British Nuclear Medicine Society / Lippincott, Williams & Wilkins

Codes

  • NII Article ID (NAID)
    120004754704
  • NII NACSIS-CAT ID (NCID)
    AA10624879
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    0143-3636
  • Data Source
    IR 
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