The aim of this study is automatic semantic segmentation and measurement total length of teeth in one-shot panoramic x-ray image by using deep learning method with U-Net Model and binary image analysis in order to provide diagnostic information for the management of dental disorders, diseases, and conditions.
This study will publish on a sciencetific journal which is Düzce Bilim ve Teknoloji Dergisi The authors of this article are Selahattin Serdar Helli and Andaç Hamamcı with the Department of Biomedical Engineering, Faculty of Engineering, Yeditepe University, Istanbul, Turkey.
U-Net Network ref - Olaf Ronneberger, Philipp Fischer, and .omas Brox, “U-net: Convolutional networks for biomedical image segmentation,” in Medical Image Computing and Computer-Assisted Intervention (MICCAI). Springer, 2015, pp. 234–241.
DATASET ref - H. Abdi, S. Kasaei, and M. Mehdizadeh, “Automatic segmentation of mandible in panoramic x-ray,” J. Med. Imaging, vol. 2, no. 4, p. 44003, 2015
Link DATASET for only original images.
Examples of Model's Outputs
Example of Final Output
Architecture.
