Treece, GM and Gee, AH and Mayhew, PM and Poole, KE (2010) High resolution cortical bone thickness measurement from clinical CT data. Med Image Anal, 14. pp. 276-290.
Full text not available from this repository.Abstract
The distribution of cortical bone in the proximal femur is believed to be a critical component in determining fracture resistance. Current CT technology is limited in its ability to measure cortical thickness, especially in the sub-millimetre range which lies within the point spread function of today's clinical scanners. In this paper, we present a novel technique that is capable of producing unbiased thickness estimates down to 0.3mm. The technique relies on a mathematical model of the anatomy and the imaging system, which is fitted to the data at a large number of sites around the proximal femur, producing around 17,000 independent thickness estimates per specimen. In a series of experiments on 16 cadaveric femurs, estimation errors were measured as -0.01+/-0.58mm (mean+/-1std.dev.) for cortical thicknesses in the range 0.3-4mm. This compares with 0.25+/-0.69mm for simple thresholding and 0.90+/-0.92mm for a variant of the 50% relative threshold method. In the clinically relevant sub-millimetre range, thresholding increasingly fails to detect the cortex at all, whereas the new technique continues to perform well. The many cortical thickness estimates can be displayed as a colour map painted onto the femoral surface. Computation of the surfaces and colour maps is largely automatic, requiring around 15min on a modest laptop computer.
| Item Type: | Article |
|---|---|
| Additional Information: | PMCID: PMC2868358 |
| Uncontrolled Keywords: | Adult Aged, 80 and over Algorithms Bone Density Computer Simulation Female Femoral Fractures Femur Humans Imaging, Three-Dimensional Male Models, Biological Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Tomography, X-Ray Computed |
| Subjects: | UNSPECIFIED |
| Divisions: | Div F > Machine Intelligence |
| Depositing User: | Cron Job |
| Date Deposited: | 28 Oct 2011 16:35 |
| Last Modified: | 17 Jun 2013 01:07 |
| DOI: | 10.1016/j.media.2010.01.003 |
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