Share Email Print

Proceedings Paper

Adaptive spectral window sizes for feature extraction from optical spectra
Author(s): Chih-Wen Kan; Andy Y. Lee; Nhi Pham; Linda T. Nieman; Konstantin Sokolov; Mia K. Markey
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

We propose an approach to adaptively adjust the spectral window size used to extract features from optical spectra. Previous studies have employed spectral features extracted by dividing the spectra into several spectral windows of a fixed width. However, the choice of spectral window size was arbitrary. We hypothesize that by adaptively adjusting the spectral window sizes, the trends in the data will be captured more accurately. Our method was tested on a diffuse reflectance spectroscopy dataset obtained in a study of oblique polarization reflectance spectroscopy of oral mucosa lesions. The diagnostic task is to classify lesions into one of four histopathology groups: normal, benign, mild dysplasia, or severe dysplasia (including carcinoma). Nine features were extracted from each of the spectral windows. We computed the area (AUC) under Receiver Operating Characteristic curve to select the most discriminatory wavelength intervals. We performed pairwise classifications using Linear Discriminant Analysis (LDA) with leave-one-out cross validation. The results showed that for discriminating benign lesions from mild or severe dysplasia, the adaptive spectral window size features achieved AUC of 0.84, while a fixed spectral window size of 20 nm had AUC of 0.71, and an AUC of 0.64 is achieved with a large window size containing all wavelengths. The AUCs of all feature combinations were also calculated. These results suggest that the new adaptive spectral window size method effectively extracts features that enable accurate classification of oral mucosa lesions.

Paper Details

Date Published: 22 February 2008
PDF: 8 pages
Proc. SPIE 6864, Biomedical Applications of Light Scattering II, 68640I (22 February 2008); doi: 10.1117/12.763927
Show Author Affiliations
Chih-Wen Kan, The Univ. of Texas (United States)
Andy Y. Lee, The Univ. of Texas at Austin (United States)
Nhi Pham, The Univ. of Texas (United States)
Linda T. Nieman, The Univ. of Texas (United States)
Konstantin Sokolov, The Univ. of Texas (United States)
Mia K. Markey, The Univ. of Texas (United States)

Published in SPIE Proceedings Vol. 6864:
Biomedical Applications of Light Scattering II
Adam Wax; Vadim Backman, Editor(s)

© SPIE. Terms of Use
Back to Top