Diagnosis of Tempromandibular Disorders Using Local Binary Patterns
محل انتشار: مجله فیزیک و مهندسی پزشکی، دوره: 8، شماره: 1
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 50
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شناسه ملی سند علمی:
JR_JBPE-8-1_009
تاریخ نمایه سازی: 30 دی 1402
چکیده مقاله:
Background: Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment.Material and Methods: CBCT images of ۶۶ patients (۱۳۲ joints) with TMD and ۶۶ normal cases (۱۳۲ joints) were collected and ۲ coronal cut prepared from each condyle, although images were limited to head of mandibular condyle. In order to extract features of images, first we use LBP and then histogram of oriented gradients. To reduce dimensionality, the linear algebra Singular Value Decomposition (SVD) is applied to the feature vectors matrix of all images. For evaluation, we used K nearest neighbor (K-NN), Support Vector Machine, Naïve Bayesian and Random Forest classifiers. We used Receiver Operating Characteristic (ROC) to evaluate the hypothesis.Results: K nearest neighbor classifier achieves a very good accuracy (۰.۹۲۴۲), moreover, it has desirable sensitivity (۰.۹۴۷۰) and specificity (۰.۹۰۱۵) results, when other classifiers have lower accuracy, sensitivity and specificity.Conclusion: We proposed a fully automatic approach to detect TMD using image processing techniques based on local binary patterns and feature extraction. K-NN has been the best classifier for our experiments in detecting patients from healthy individuals, by ۹۲.۴۲% accuracy, ۹۴.۷۰% sensitivity and ۹۰.۱۵% specificity. The proposed method can help automatically diagnose TMD at its initial stages.
کلیدواژه ها:
Temporomandibular Joint Disorder ، Cone-Beam Computed Tomography ، Local Binary Pattern ، Histogram of Oriented Gradients ، K Nearest Neighbor
نویسندگان
A A Haghnegahdar
Department of Oral & Maxillofacial Radiology, school of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran
S Kolahi
Department of Oral & Maxillofacial Radiology, school of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran
L Khojastepour
Department of Oral & Maxillofacial Radiology, school of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran
F Tajeripour
Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
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