Computer-Aided System of the Mandibular Cortical Bone Porosity Assessment on Digital Panoramic Radiographs

• Main Authors: Eha Renwi Astuti, -, Agus Z. Arifin, -, Rarasmaya Indraswari, -, Ramadhan H. Putra, -
• Format: Article PeerReviewed
• Language: English; English; Indonesian; English
• Published: Georg Thieme Verlag 2021
• Subjects: R Medicine; RK Dentistry
• Online Access: https://repository.unair.ac.id/118015/2/1.%20Computer-Aided%20System%20of%20the%20Mandibular.pdf; https://repository.unair.ac.id/118015/3/1.%2017%25%20Computer-Aided%20System%20of%20the%20Mandibular%20Cortical%20Bone%20Porosity%20Assessment%20on%20Digital%20Panoramic%20Radiographs.pdf; https://repository.unair.ac.id/118015/4/1.%20Computer-Aided%20System%20of%20the%20Mandibular%20Cortical%20Bone%20Porosity%20Assessment%20on%20Digital%20Panoramic%20Radiographs.pdf; https://repository.unair.ac.id/118015/8/1.%20Computer-aided%20system%20of%20the%20mandibular.pdf; https://repository.unair.ac.id/118015/; https://doi.org/ 10.1055/s-0042-1749158
• Institution: Universitas Airlangga

Objectives The loss of bone mineral density (BMD) in various sites of the body, including the mandible, is the main sign of osteoporosis. Thus, the computer-aided diagnosis (CAD) system was developed for bone density assessment and patients were classified into normal, osteopenia, and osteoporosis groups using a digital panoramic radiograph. Material and Methods Data of dental panoramic radiographs and corresponding BMD assessments from 123 postmenopausal women were collected. For the proposed CAD system test, regions of interest (ROI) that were located below the left and right mental foramen on dental panoramic radiographs were determined. The width and texture of the mandibular cortical bone in each ROI were used to classify the data into normal, osteopenia, and osteoporosis classes. The width of the mandibular cortical was measured using the polynomial fittingmethod. The texture feature of the cortical bone is obtained by calculating the average value of the grayscale intensity of cortical bone. The classification result was obtained by using a multiclass support vector machine. Results The experimental results using 10-fold cross-validation showed that the proposed system achieved an average accuracy of 86.50% for osteoporosis classification on dental panoramic radiographs. The average misclassification error and relative foreground area error of the segmentation process were 5.21 and 12.98%, respectively. From the analysis of the cortical width measurement process, highest average mandibular cortical width (MCW) was found in the normal patient category compared with the other classes.