• DocumentCode
    745340
  • Title

    A novel local thresholding algorithm for trabecular bone volume fraction mapping in the limited spatial resolution regime of in vivo MRI

  • Author

    Vasilic, Branimir ; Wehrli, Felix W.

  • Author_Institution
    Dept. of Radiol., Univ. of Pennsylvania Med. Center, Philadelphia, PA, USA
  • Volume
    24
  • Issue
    12
  • fYear
    2005
  • Firstpage
    1574
  • Lastpage
    1585
  • Abstract
    Recent advances in micro-magnetic resonance imaging have shown the possibility of in vivo assessment of trabecular bone architecture. However, the small feature size and relatively low signal-to-noise ratio (SNR) achievable in vivo cause the intensity histogram to be unimodal. The critical first step in the processing of these images is the extraction of bone volume fraction for each voxel. Here, we propose a local threshold algorithm (LTA) that determines the marrow intensity value in the neighborhood of each voxel based on nearest-neighbor statistics. Using the local marrow intensities we threshold the image and scale the intensities of voxels partially occupied by bone to produce a marrow volume fraction map of the trabecular bone region. We show that structural parameters derived with the LTA are highly correlated with those obtained with the previously published histogram deconvolution algorithm (HDA) and that the LTA is robust to image noise corruption. The LTA is found to correctly identify trabeculae with a significantly higher reliability than HDA. Finally, we demonstrate that the LTA is superior in preserving connectivity by showing for 75 in vivo images that the genus of the trabecular bone surface is always higher than when processed with the HDA.
  • Keywords
    biomedical MRI; bone; deconvolution; image resolution; medical image processing; bone volume fraction extraction; histogram deconvolution algorithm; image noise corruption; image processing; in vivo MRI; limited spatial resolution; local marrow intensities; local thresholding algorithm; micro-magnetic resonance imaging; nearest-neighbor statistics; trabecular bone volume fraction mapping; Cancellous bone; Deconvolution; Histograms; In vivo; Magnetic resonance imaging; Noise robustness; Signal to noise ratio; Spatial resolution; Statistics; Structural engineering; Image segmentation; local; threshold; trabecular bone; Algorithms; Artificial Intelligence; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Organ Size; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Tibia;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2005.859192
  • Filename
    1546119