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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Mohammed Ed-Dhahraouy
Chouaib Doukkali University
Computer Science & IT Electrical & Electronics Engineering

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Extracted features based multi-class classification of orthodontic images Hicham Riri; Mohammed Ed-Dhahraouy; Abdelmajid Elmoutaouakkil; Abderrahim Beni-Hssane; Farid Bourzgui
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (966.976 KB) | DOI: 10.11591/ijece.v10i4.pp3558-3567

Abstract

The purpose of this study is to investigate computer vision and machine learning methods for classification of orthodontic images in order to provide orthodontists with a solution for multi-class classification of patients’ images to evaluate the evolution of their treatment. Of which, we proposed three algorithms based on extracted features, such as facial features and skin colour using YCbCrcolour space, assigned to nodes of a decision tree to classify orthodontic images: an algorithm for intra-oral images, an algorithm for mould images and an algorithm for extra-oral images. Then, we compared our method by implementing the Local Binary Pattern (LBP) algorithm to extract textural features from images. After that, we applied the principal component analysis (PCA) algorithm to optimize the redundant parameters in order to classify LBP features with six classifiers; Quadratic Support Vector Machine (SVM), Cubic SVM, Radial Basis Function SVM, Cosine K-Nearest Neighbours (KNN), Euclidian KNN, and Linear Discriminant Analysis (LDA). The presented algorithms have been evaluated on a dataset of images of 98 different patients, and experimental results demonstrate the good performances of our proposed method with a high accuracy compared with machine learning algorithms. Where LDA classifier achieves an accuracy of 84.5%.
The contribution of image processing in the evaluation of guided bone regeneration Hamid El Byad; Manal Ezzahmouly; Mohammed Ed-Dhahraouy; Abdelmajid El Moutaouakkil; Zineb Hatim
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5795

Abstract

One of the most ambitious goals of modern bone surgery is to predict the shape of the bone defect, monitor the progress of bone regeneration, and assess the quantity and quality of newly formed bone. Calcium phosphate biomaterials such as hydroxyapatite and tricalcium phosphate are commonly used as bone substitutes in maxillofacial and dental surgery. The objective of this work is to use cone-beam computed tomography (CBCT) and image processing to assess the spatial (architectural) layout, rate of bone generation and osseointegration of implanted commercial granules (PAH 40%, β-TCP 60%, size 0.5 to 1 mm) in the bone defect generated after tooth extraction. CBCT measurements were performed at 48 hours and 12 months. The analysis of 3D images and the application of appropriate morphological mathematical operations allowed us to evaluate the volume of the cavity to be filled, the volume occupied by the granules and the volume of porosity generated by the random stacking of the granules. The result shows that the bone generation rate reaches a value of 89% after one year of implantation. This study shows that by using 3D image processing techniques CBCT, the same results as classical anatomical and histological studies can be obtained.
Co-Authors Abdelmajid El Moutaouakkil Abdelmajid Elmoutaouakkil Abderrahim Beni-Hssane Farid Bourzgui Hamid El Byad Hicham Riri Manal Ezzahmouly Zineb Hatim