Asymmetry analysis based on genetic algorithms for the prediction of foot ulcers

Naima Kaabouch; Yi Chen; Julie Anderson; Forrest Ames; Rolf Paulson

doi:10.1117/12.805975

20 January 2009 Asymmetry analysis based on genetic algorithms for the prediction of foot ulcers

Naima Kaabouch, Yi Chen, Julie Anderson, Forrest Ames, Rolf Paulson

Proceedings Volume 7243, Visualization and Data Analysis 2009; 724304 (2009) https://doi.org/10.1117/12.805975
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

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.

Citation Download Citation

Naima Kaabouch, Yi Chen, Julie Anderson, Forrest Ames, and Rolf Paulson "Asymmetry analysis based on genetic algorithms for the prediction of foot ulcers", Proc. SPIE 7243, Visualization and Data Analysis 2009, 724304 (20 January 2009); https://doi.org/10.1117/12.805975

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