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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.
Date of Publication: Dec. 2005