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Proceedings Paper

Asymmetry analysis based on genetic algorithms for the prediction of foot ulcers
Author(s): Naima Kaabouch; Yi Chen; Julie Anderson; Forrest Ames; Rolf Paulson
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Paper Abstract

Foot ulcers affect millions of Americans annually. Conventional methods to assess skin, including inspection and palpation, may be valuable approaches, but usually they do not detect changes in skin integrity until an ulcer has already developed. Conversely, thermal imaging is a technology able to assess the integrity of the skin and its many layers, thus having the potential to index the cascade of physiological events in the prevention, assessment, and management of foot ulcers. In this paper, we propose a methodology based on an asymmetry analysis and a genetic algorithm to analyze the infrared images for early detection of foot ulcers. Preliminary results show that the proposed technique can be reliable and efficient to detect and, hence, predict inflammation and potential ulceration.

Paper Details

Date Published: 20 January 2009
PDF: 6 pages
Proc. SPIE 7243, Visualization and Data Analysis 2009, 724304 (20 January 2009); doi: 10.1117/12.805975
Show Author Affiliations
Naima Kaabouch, Univ. of North Dakota (United States)
Yi Chen, Univ. of North Dakota (United States)
Julie Anderson, Univ. of North Dakota (United States)
Forrest Ames, Univ. of North Dakota (United States)
Rolf Paulson, Altru Wound Clinic (United States)


Published in SPIE Proceedings Vol. 7243:
Visualization and Data Analysis 2009
Katy Börner; Jinah Park, Editor(s)

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