title: Estimating rheumatoid arthritis activity with infrared image analysis.
abstract: This work describes the development of a new diagnostic tool to assess the severity of rheumatoid arthritis (RA) using infrared image collection and analysis. Early work showed that the temperature distribution of joints of hands and knees of patients with RA was statistically significantly different from that of normal subjects. Current work identified ankles as also significant for an assessment of RA. Moreover, the patients were classified in three levels of RA severity (High, Medium, and Low) using a C5.0 decision tree classifier with excellent results: Sensitivity (true positive cases) of 96 % and a specificity (true negative cases) of 92%. Future work will automate the image analysis and test clinically by comparing to MR as ground truth.
authors.affiliation: Carleton University, Systems and Comp. Eng., Ottawa, Ontario, Canada. mfrize@gmail.com
authors.forename: Monique
authors.initials: M
authors.lastname: Frize
authors.forename: Abiola
authors.initials: A
authors.lastname: Ogungbemile
mesh_terms: D000465:Algorithms; D001172:Arthritis, Rheumatoid / Q000175:diagnosis*; D001185:Artificial Intelligence; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013817:Thermography / Q000379:methods*