title: Computer-aided diagnosis of rheumatoid arthritis with optical tomography, Part 2: image classification.
abstract: This is the second part of a two-part paper on the application of computer-aided diagnosis to diffuse optical tomography (DOT) for diagnosing rheumatoid arthritis (RA). A comprehensive analysis of techniques for the classification of DOT images of proximal interphalangeal joints of subjects with and without RA is presented. A method for extracting heuristic features from DOT images was presented in Part 1. The ability of five classification algorithms to accurately label each DOT image as belonging to a subject with or without RA is analyzed here. The algorithms of interest are the k-nearest-neighbors, linear and quadratic discriminant analysis, self-organizing maps, and support vector machines (SVM). With a polynomial SVM classifier, we achieve 100.0% sensitivity and 97.8% specificity. Lower bounds for these results (at 95.0% confidence level) are 96.4% and 93.8%, respectively. Image features most predictive of RA are from the spatial variation of optical properties and the absolute range in feature values. The optimal classifiers are low-dimensional combinations (<7 features). These results underscore the high potential for DOT to become a clinically useful diagnostic tool and warrant larger prospective clinical trials to conclusively demonstrate the ultimate clinical utility of this approach.
authors.affiliation: Department of Biomedical Engineering, Columbia University, New York, New York 10025, USA. ldm2106@columbia.edu
authors.forename: Ludguier D
authors.initials: LD
authors.lastname: Montejo
authors.forename: Jingfei
authors.initials: J
authors.lastname: Jia
authors.forename: Hyun K
authors.initials: HK
authors.lastname: Kim
authors.forename: Uwe J
authors.initials: UJ
authors.lastname: Netz
authors.forename: Sabine
authors.initials: S
authors.lastname: Blaschke
authors.forename: Gerhard A
authors.initials: GA
authors.lastname: Müller
authors.forename: Andreas H
authors.initials: AH
authors.lastname: Hielscher
mesh_terms: D001172:Arthritis, Rheumatoid / Q000175:diagnosis*; D016002:Discriminant Analysis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D060388:Support Vector Machine; D041622:Tomography, Optical / Q000379:methods*