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Proceedings Paper

Multi-parameter optical image interpretations based on self-organizing mapping
Author(s): Christian D. Klose; A. K. Klose; U. Netz; A. Scheel; J. Beuthan; Andreas H. Hielscher
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Paper Abstract

We found that using more than one parameter derived from optical tomographic images can lead to better image classification results compared to cases when only one parameter is used.. In particular we present a multi-parameter classification approach, called self-organizing mapping (SOM), for detecting synovitis in arthritic finger joints based on sagittal laser optical tomography (SLOT). This imaging modality can be used to determine various physical parameters such as minimal absorption and scattering coefficients in an image of the proximal interphalengeal joint. Results were compared to different gold standards: magnet resonance imaging, ultra-sonography and clinical evaluation. When compared to classifications based on single-parameters, e.g., absorption minimum only, the study reveals that multi-parameter classifications lead to higher classification sensitivities and specificities and statistical significances with p-values <5 per cent. Finally, the data suggest that image analyses are more reliable and avoid ambiguous interpretations when using more than one parameter.

Paper Details

Date Published: 7 March 2008
PDF: 6 pages
Proc. SPIE 6850, Multimodal Biomedical Imaging III, 68500G (7 March 2008); doi: 10.1117/12.763680
Show Author Affiliations
Christian D. Klose, Columbia Univ. (United States)
A. K. Klose, Columbia Univ. (United States)
U. Netz, Charité - Universitätsmedizin Berlin (Germany)
A. Scheel, George-August-Univ. Göttingen (Germany)
J. Beuthan, Charité - Universitätsmedizin Berlin (Germany)
Andreas H. Hielscher, Columbia Univ. (United States)

Published in SPIE Proceedings Vol. 6850:
Multimodal Biomedical Imaging III
Fred S. Azar; Xavier Intes, Editor(s)

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