Rule-Based Fuzzy Classifier for Spinal Deformities
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Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IOS Press
Open Access Color
BRONZE
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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Impulse
Average
Influence
Average
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Average
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.
Description
Korkmaz, Hayriye/0000-0002-5994-7587; Birtane Akar, Sibel/0000-0002-4921-1381
Keywords
Image Processing, Scoliosis, King-Moe Type Classification, Fuzzy Logic, Computer Aided Classification, Rule-Based Classification, Image Processing, Computer Aided Classification, Reproducibility of Results, Rule-Based Classification, Sensitivity and Specificity, 004, Pattern Recognition, Automated, Radiographic Image Enhancement, Fuzzy Logic, Scoliosis, Artificial Intelligence, King-Moe Type Classification, Humans, Radiographic Image Interpretation, Computer-Assisted, Algorithms
Fields of Science
03 medical and health sciences, 0302 clinical medicine
Citation
WoS Q
Q4
Scopus Q
Q4
OpenCitations Citation Count
4
Source
Bio-Medical Materials and Engineering
Volume
24
Issue
6
Start Page
3311
End Page
3319
PlumX Metrics
Citations
CrossRef : 2
Scopus : 3
PubMed : 1
Captures
Mendeley Readers : 25
SCOPUS™ Citations
3
checked on Feb 28, 2026
Web of Science™ Citations
2
checked on Feb 28, 2026
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