Adaptive spectral window sizes for feature extraction from optical spectra

Chih-Wen Kan; Andy Y. Lee; Nhi Pham; Linda T. Nieman; Konstantin Sokolov; Mia K. Markey

doi:10.1117/12.763927

22 February 2008 Adaptive spectral window sizes for feature extraction from optical spectra

Chih-Wen Kan, Andy Y. Lee, Nhi Pham, Linda T. Nieman, Konstantin Sokolov, Mia K. Markey

Proceedings Volume 6864, Biomedical Applications of Light Scattering II; 68640I (2008) https://doi.org/10.1117/12.763927
Event: SPIE BiOS, 2008, San Jose, California, United States

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.

Citation Download Citation

Chih-Wen Kan, Andy Y. Lee, Nhi Pham, Linda T. Nieman, Konstantin Sokolov, and Mia K. Markey "Adaptive spectral window sizes for feature extraction from optical spectra", Proc. SPIE 6864, Biomedical Applications of Light Scattering II, 68640I (22 February 2008); https://doi.org/10.1117/12.763927

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Feature extraction

Diagnostics

Adaptive optics

Diffuse reflectance spectroscopy

Visualization

Feature selection

Principal component analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years