Classification of Oral Cavity Using the Convolution Neural Network
1Ayat A. Yosif, Musa K. Mohsin Khalil, Hussain Muhyi Ali
The oral cavity is known as the zone between the lips and the finish of the hard sense of taste. Contains teeth, buccal mucosa and gums, lower jaw and hard sense of taste, floor of the mouth and foremost tongue of the papilla around the papilla. This work describes an automatic classification algorithm that classifies of the Cinnamon contact stomatitis and Leukoedema of the buccal mucosa. Methods: The data set contains 20 images categorized into two types of diseases. Divide The informational index was partitioned into two preparing parts and a test part in this study. Results: Convolution neural network (CNN) technology was used on data. Two types of jaw diseases have been taken, which are diseases that appear in the oral cavity, which are apparent and not within the tissues, and that appear in the true form to the jaw. Conclusions: Cinnamon contact dermatitis and white edema of the buccal mucosa it can be detected with CNN with accuracy similar to that in manual diagnosis by maxillofacial specialists.
Image Classification, Convolutional Neural Networks (CNN), Cinnamon contact stomatitis, Leukoedema of the buccal mucosa, Image Processing.