
Proceedings Paper
Quantitative confirmation of visual improvements to micro-CT bone density imagesFormat | Member Price | Non-Member Price |
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Paper Abstract
The primary goal of this research was to investigate the ability of quantitative variables to
confirm qualitative improvements of the deconvolution algorithm as a preprocessing step in
evaluating micro CT bone density images. The analysis of these types of images is important
because they are necessary to evaluate various countermeasures used to reduce or potentially
reverse bone loss experienced by some astronauts when exposed to extended weightlessness during
space travel. Nine low resolution (17.5 microns) CT bone density image sequences, ranging from
between 85 to 88 images per sequence, were processed with three preprocessing treatment groups
consisting of no preprocessing, preprocessing with a deconvolution algorithm and preprocessing
with a Gaussian filter. The quantitative parameters investigated consisted of Bone Volume to Total
Volume Ratio, the Structured Model Index, Fractal Dimension, Bone Area Ratio, Bone Thickness
Ratio, Euler's Number and the Measure of Enhancement. Trends found in these quantitative
variables appear to corroborate the visual improvements observed in the past and suggest which
quantitative parameters may be capable of distinguishing between groups that experience bone loss
and others that do not..
Paper Details
Date Published: 12 May 2006
PDF: 9 pages
Proc. SPIE 6246, Visual Information Processing XV, 62460D (12 May 2006); doi: 10.1117/12.661306
Published in SPIE Proceedings Vol. 6246:
Visual Information Processing XV
Zia-ur Rahman; Stephen E. Reichenbach; Mark A. Neifeld, Editor(s)
PDF: 9 pages
Proc. SPIE 6246, Visual Information Processing XV, 62460D (12 May 2006); doi: 10.1117/12.661306
Show Author Affiliations
John S. DaPonte, Southern Connecticut State Univ. (United States)
Michael Clark, Southern Connecticut State Univ. (United States)
Paul Nelson, Southern Connecticut State Univ. (United States)
Michael Clark, Southern Connecticut State Univ. (United States)
Paul Nelson, Southern Connecticut State Univ. (United States)
Thomas Sadowski, Southern Connecticut State Univ. (United States)
Elizabeth Wood, Southern Connecticut State Univ. (United States)
Elizabeth Wood, Southern Connecticut State Univ. (United States)
Published in SPIE Proceedings Vol. 6246:
Visual Information Processing XV
Zia-ur Rahman; Stephen E. Reichenbach; Mark A. Neifeld, Editor(s)
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