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A New Algorithm for Cortical Bone Segmentation with Its Validation and Applications to In Vivo Imaging

  • Cheng Li
  • Dakai Jin
  • Trudy L. Burns
  • James C. Torner
  • Steven M. Levy
  • Punam K. Saha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

Cortical bone supports and protects our skeletal functions and it plays an important in determining bone strength and fracture risks. Cortical bone segmentation is needed for quantitative analyses and the task is nontrivial for in vivo multi-row detector CT (MD-CT) imaging due to limited resolution and partial volume effects. An automated cortical bone segmentation algorithm for in vivo MD-CT imaging of distal tibia is presented. It utilizes larger contextual and topologic information of the bone using a modified fuzzy distance transform and connectivity analyses. An accuracy of 95.1% in terms of volume of agreement with true segmentations and a repeat MD-CT scan intra-class correlation of 98.2% were observed in a cadaveric study. An in vivo study involving 45 age-similar and height-matched pairs of male and female volunteers has shown that, on an average, male subjects have 16.3% thicker cortex and 4.7% increased porosity as compared to females.

Keywords

Osteoporosis cortical bone segmentation CT imaging fuzzy distance transform connectivity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Cheng Li
    • 1
  • Dakai Jin
    • 1
  • Trudy L. Burns
    • 2
  • James C. Torner
    • 2
  • Steven M. Levy
    • 2
    • 3
  • Punam K. Saha
    • 1
    • 4
  1. 1.Department of Electrical and Computer EngineeringUniversity of IowaIowa CityUSA
  2. 2.Department of EpidemiologyUniversity of IowaIowa CityUSA
  3. 3.College of DentistryUniversity of IowaIowa CityUSA
  4. 4.Department of RadiologyUniversity of IowaIowa CityUSA

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