Quantum Particle Swarm Optimization for Multilevel Thresholding-Based Image Segmentation on Dental X-Ray Images

Dental radiographic images play an important role by assisting dentist to diagnose and treat a wide range of dental diseases and anomalies. Automatic analysis of radiographs can lead to efficient and accurate diagnosis of dental problems. Teeth segmentation of panoramic radiographs is one of the most crucial tasks to localize impacted teeth, identify untreated root canals and to detect fractured teeth. Multilevel thresholding based image segmentation is considered here to segment the teeth from the dental x-ray images. In this paper, a quantum computing based computational intelligence technique i.e. quantum particle swarm optimization (QPSO) is introduced for multilevel image thresholding of dental x-ray images. Results demonstrate that the proposed method provides a useful and reliable tool for such multilevel thresholding based image segmentation.