CONFERENCE PROCEEDINGS
Advanced Search
Home > Journals > J. Biomed. Opt. > Volume 18 > Issue 7 > Article
Open Access
15 July 2013 Computer-aided diagnosis of rheumatoid arthritis with optical tomography, Part 1: feature extraction
Ludguier D. Montejo, Jingfei Jia, Hyun K. Kim, Uwe J. Netz, Sabine Blaschke, Gerhard A. Mueller, Andreas H. Hielscher
Author Affiliations +
Journal of Biomedical Optics, Vol. 18, Issue 7, 076001 (July 2013). https://doi.org/10.1117/1.JBO.18.7.076001
Abstract
This is the first part of a two-part paper on the application of computer-aided diagnosis to diffuse optical tomography (DOT). An approach for extracting heuristic features from DOT images and a method for using these features to diagnose rheumatoid arthritis (RA) are presented. Feature extraction is the focus of Part 1, while the utility of five classification algorithms is evaluated in Part 2. The framework is validated on a set of 219 DOT images of proximal interphalangeal (PIP) joints. Overall, 594 features are extracted from the absorption and scattering images of each joint. Three major findings are deduced. First, DOT images of subjects with RA are statistically different (p<0.05 ) from images of subjects without RA for over 90% of the features investigated. Second, DOT images of subjects with RA that do not have detectable effusion, erosion, or synovitis (as determined by MRI and ultrasound) are statistically indistinguishable from DOT images of subjects with RA that do exhibit effusion, erosion, or synovitis. Thus, this subset of subjects may be diagnosed with RA from DOT images while they would go undetected by reviews of MRI or ultrasound images. Third, scattering coefficient images yield better one-dimensional classifiers. A total of three features yield a Youden index greater than 0.8. These findings suggest that DOT may be capable of distinguishing between PIP joints that are healthy and those affected by RA with or without effusion, erosion, or synovitis.
© 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2013/$25.00 © 2013 SPIE
Citation Download Citation
Ludguier D. Montejo, Jingfei Jia, Hyun K. Kim, Uwe J. Netz, Sabine Blaschke, Gerhard A. Mueller, and Andreas H. Hielscher "Computer-aided diagnosis of rheumatoid arthritis with optical tomography, Part 1: feature extraction," Journal of Biomedical Optics 18(7), 076001 (15 July 2013). https://doi.org/10.1117/1.JBO.18.7.076001
Published: 15 July 2013
JOURNAL ARTICLE
 14 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Lens.org Logo
CITATIONS
Cited by 31 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Computer aided diagnosis and therapy
Feature extraction
Magnetic resonance imaging
Selenium
Data modeling
Optical tomography
Ultrasonography
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top