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Enhancement of the asymmetry-based overlapping analysis through features extraction

[+] Author Affiliations
Naima Kaabouch

University of North Dakota, Electrical Engineering Department, Grand Forks, North Dakota 58202

Yi Chen

University of North Dakota, Electrical Engineering Department, Grand Forks, North Dakota 58202

Wen-Chen Hu

University of North Dakota, Computer Science Department, Grand Forks, North Dakota 58202

Julie W. Anderson

University of North Dakota, College of Nursing, Grand Forks, North Dakota 58202

Forrest Ames

University of North Dakota, Mechanical Engineering Department, Grand Forks, North Dakota 58202

Rolf Paulson

Altru Wound Clinic, Grand Forks, North Dakota 58201

J. Electron. Imaging. 20(1), 013012 (March 22, 2011). doi:10.1117/1.3553240
History: Received July 01, 2009; Revised January 04, 2011; Accepted January 06, 2011; Published March 22, 2011; Online March 22, 2011
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In this paper, an enhanced algorithm is proposed to detect foot inflammation and, hence, predict ulcers before they can develop. This algorithm is based on an asymmetry analysis combined with a segmentation technique with a genetic algorithm to achieve higher efficiency in the detection of inflammation. The analysis involves several steps: segmentation, geometry transformation, overlapping, and abnormality identification. To enhance the results of this analysis, an additional step, features extraction, is performed. In this step, low and high order statistics are computed for each foot. Preliminary results show that the proposed algorithm combined with features extraction can be reliable and efficient to predict potential ulceration.

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© 2011 SPIE and IS&T

Citation

Naima Kaabouch ; Yi Chen ; Wen-Chen Hu ; Julie W. Anderson ; Forrest Ames, et al.
"Enhancement of the asymmetry-based overlapping analysis through features extraction", J. Electron. Imaging. 20(1), 013012 (March 22, 2011). ; http://dx.doi.org/10.1117/1.3553240


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