ACSDI An Approach of Clustering Stream Dental Panoramic Images - Ammar Thaher Yaseen Al Abd Alazeez (PROSPECTIVE RESEARCHES, 2023)
In this paper we developed a simple computer-aided program that could help detect and count the teeth by proposing clustering stream tooth segmentation and counting method. The automatic solution to segment and count the teeth from the dental panoramic X-ray images is based on machine learning and geometrical features. We segment and enhance the teeth region using the mask technique and check the reliability of the result image using BHPF filter. We depend on a collected and filtered 50 X-ray panoramic database images from the dentist websites. MATLAB was utilized to develop proposed ACSDI method and the experiments. The results show that our proposed algorithm superiority existing ones in both sensitivity and specificity which are above 70% for reliable counting and above 50% for unreliable counting. This study provides data which can be used in treatment planning by specialists such as orthodontists, plastic and surgeons who have the capability to change the facial features.