Automated Teeth Extraction from Dental Panoramic X-Ray Images using Genetic Algorithm

Dental x-ray imaging helps dentists and radiologists to diagnose dental diseases and to provide patients with treatment plannings. In many cases, dental diseases are hard to detect by relying only on visual inspection. Therefore, automating the diagnosis process has been a topic of interest for dental problems. Teeth extraction is the basic task needed for nearly all dentistry decision support systems relying on radiographic images as the inputs. The most challenging type of image to perform extraction on is the panoramic image since it includes other parts of the patient's mouth, and structures lack explicit boundaries. The proposed method in this paper is the first automated teeth extraction system from dental panoramic images using evolutionary algorithms. First, the jaw is extracted from the main image. Then, upper and lower jaws are separated, followed by a genetic algorithm to detect teeth gap valleys. The method is assessed applying to 42 images, where the perceived accuracy is 81.14% for upper jaws and 73.63% for lower jaws, which is comparable with previous methods used on more straightforward image types.