title: Rule-based fuzzy classifier for spinal deformities.
abstract: In this paper, 2-steps software using image processing and enhancement technologies is developed to obtain a scoliosis patient's spine pattern from 2D coronal X-Ray images without manual land marking. Then, a Rule-based Fuzzy classifier is implemented on those images to classify the spine patterns using the King-Moe classification approach.
authors.affiliation: Department of Computer Programming, Vocational School, Istanbul Arel University, Istanbul, Turkey.
authors.forename: Sibel
authors.initials: S
authors.lastname: Birtane
authors.affiliation: Department of Electrical and Electronics Engineering, Faculty of Technology, Marmara University, Istanbul, Turkey.
authors.forename: Hayriye
authors.initials: H
authors.lastname: Korkmaz
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D017143:Fuzzy Logic; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012600:Scoliosis / Q000000981:diagnostic imaging*; D012680:Sensitivity and Specificity
keywords: Image processing; computer aided classification; fuzzy logic; king-moe type classification; rule-based classification; scoliosis