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Erschienen in:
2013 | OriginalPaper | Buchkapitel
A New Algorithm for Cortical Bone Segmentation with Its Validation and Applications to In Vivo Imaging
verfasst von : Cheng Li, Dakai Jin, Trudy L. Burns, James C. Torner, Steven M. Levy, Punam K. Saha
Erschienen in: Image Analysis and Processing – ICIAP 2013
Verlag: Springer Berlin Heidelberg
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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.