Rule-based fuzzy classifier for spinal deformities
Copyright policy )Rule-based fuzzy classifier for spinal deformities
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.
- Istanbul Arel University Turkey
- Marmara University Turkey
INTEROBSERVER, Image Processing, Rule-Based Classification, king-moe type classification, Sensitivity and Specificity, Pattern Recognition, Automated, Image processing, Fuzzy Logic, Artificial Intelligence, Humans, SCOLIOSIS, scoliosis, Computer Aided Classification, Reproducibility of Results, 004, Radiographic Image Enhancement, INTRAOBSERVER, Scoliosis, rule-based classification, RELIABILITY, King-Moe Type Classification, computer aided classification, Radiographic Image Interpretation, Computer-Assisted, fuzzy logic, Algorithms
INTEROBSERVER, Image Processing, Rule-Based Classification, king-moe type classification, Sensitivity and Specificity, Pattern Recognition, Automated, Image processing, Fuzzy Logic, Artificial Intelligence, Humans, SCOLIOSIS, scoliosis, Computer Aided Classification, Reproducibility of Results, 004, Radiographic Image Enhancement, INTRAOBSERVER, Scoliosis, rule-based classification, RELIABILITY, King-Moe Type Classification, computer aided classification, Radiographic Image Interpretation, Computer-Assisted, fuzzy logic, Algorithms
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