Analysis and classification of optical tomographic images of rheumatoid fingers with ANOVA and discriminate analysis

Ludguier D. Montejo; Hyun K. Kim; Yrjö Häme; Jingfei Jia; Julio D. Montejo; Uwe J. Netz; Sabine Blaschke; Paul Zwaka; Gerhard A. Müeller; Jürgen Beuthan; Andreas H. Hielscher

doi:10.1117/12.875977

21 February 2011 Analysis and classification of optical tomographic images of rheumatoid fingers with ANOVA and discriminate analysis

Ludguier D. Montejo, Hyun K. Kim, Yrjö Häme, Jingfei Jia, Julio D. Montejo, Uwe J. Netz, Sabine Blaschke, Paul Zwaka, Gerhard A. Müeller, Jürgen Beuthan, Andreas H. Hielscher

Author Affiliations +

Proceedings Volume 7890, Advanced Biomedical and Clinical Diagnostic Systems IX; 78900L (2011) https://doi.org/10.1117/12.875977
Event: SPIE BiOS, 2011, San Francisco, California, United States

Abstract

We present a study on the effectiveness of computer-aided diagnosis (CAD) of rheumatoid arthritis (RA) from frequency-domain diffuse optical tomographic (FDOT) images. FDOT is used to obtain the distribution of tissue optical properties. Subsequently, the non-parametric Kruskal-Wallis ANOVA test is employed to verify statistically significant differences between the optical parameters of patients affected by RA and healthy volunteers. Furthermore, quadratic discriminate analysis (QDA) of the absorption (μ_a) and scattering (μ_a or μ'_s) distributions is used to classify subjects as affected or not affected by RA. We evaluate the classification efficiency by determining the sensitivity (Se), specificity (Sp), and the Youden index (Y). We find that combining features extracted from μ_a and μ_a or μ'_s images allows for more accurate classification than when μ_a or μ_a or μ'_s features are considered individually on their own. Combining μ_a and μ_a or μ'_s features yields values of up to Y = 0.75 (Se = 0.84 and Sp = 0.91). The best results when μ_a or μ'_s features are considered individually are Y = 0.65 (Se = 0.85 and Sp = 0.80) and Y = 0.70 (Se = 0.80 and Sp = 0.90), respectively.

Citation Download Citation

Ludguier D. Montejo, Hyun K. Kim, Yrjö Häme, Jingfei Jia, Julio D. Montejo, Uwe J. Netz, Sabine Blaschke, Paul Zwaka, Gerhard A. Müeller, Jürgen Beuthan, and Andreas H. Hielscher "Analysis and classification of optical tomographic images of rheumatoid fingers with ANOVA and discriminate analysis", Proc. SPIE 7890, Advanced Biomedical and Clinical Diagnostic Systems IX, 78900L (21 February 2011); https://doi.org/10.1117/12.875977

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
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Selenium

Absorption

Data analysis

Image classification

Scattering

Tissue optics

Feature extraction

Show All Keywords

Keywords/Phrases

Search In:

Publication Years