Research Papers: Sensing

Adaptive spectral window sizes for extraction of diagnostic features from optical spectra

[+] Author Affiliations
Chih-wen Kan, Andy Y. Lee

The University of Texas, Department of Biomedical Engineering, 1 University Station, Austin, Texas 78712-1084

Linda T. Nieman, Konstantin Sokolov

The University of Texas, Department of Biomedical Engineering, 1 University Station, Austin, Texas 78712-1084 and The University of Texas, M. D. Anderson Cancer Center, Department of Imaging Physics, 1515 Holcombe Boulevard, Houston, Texas 77030

Mia K. Markey

The University of Texas, Department of Biomedical Engineering, 1 University Station, Austin, Texas 78712-1084

J. Biomed. Opt. 15(4), 047012 (August 20, 2010). doi:10.1117/1.3481143
History: Received April 18, 2010; Revised June 26, 2010; Accepted July 01, 2010; Published August 20, 2010; Online August 20, 2010
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We present an approach to adaptively adjust the spectral window sizes for optical spectra feature extraction. Previous studies extracted features from spectral windows of a fixed width. In our algorithm, piecewise linear regression is used to adaptively adjust the window sizes to find the maximum window size with reasonable linear fit with the spectrum. This adaptive windowing technique ensures the signal linearity in defined windows; hence, the adaptive windowing technique retains more diagnostic information while using fewer windows. This method was tested on a data set of diffuse reflectance spectra of oral mucosa lesions. Eight features were extracted from each window. We performed classifications using linear discriminant analysis with cross-validation. Using windowing techniques results in better classification performance than not using windowing. The area under the receiver-operating-characteristics curve for windowing techniques was greater than a nonwindowing technique for both normal versus mild dysplasia (MD) plus severe high-grade dysplasia or carcinama (SD) (MD+SD) and benign versus MD+SD. Although adaptive and fixed-size windowing perform similarly, adaptive windowing utilizes significantly fewer windows than fixed-size windows (number of windows per spectrum: 8 versus 16). Because adaptive windows retain most diagnostic information while reducing the number of windows needed for feature extraction, our results suggest that it isolates unique diagnostic features in optical spectra.

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© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Chih-wen Kan ; Andy Y. Lee ; Linda T. Nieman ; Konstantin Sokolov and Mia K. Markey
"Adaptive spectral window sizes for extraction of diagnostic features from optical spectra", J. Biomed. Opt. 15(4), 047012 (August 20, 2010). ; http://dx.doi.org/10.1117/1.3481143


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