Evaluation of Dental Implant for Surgical Planning and Complications by Using Optimized CBCT Images

Abstract

Modern dentistry has made tremendous advances in dental materials, procedures and strategies that are highly effective in the long-term management of tooth loss. Patients who have lost all or part of their teeth can now have them replaced with dental implants that provide the same function and appearance as their natural teeth. However, the procedure of dental implant itself is complex subject and requires years of experience and expertise. The radiological assessment is an essential part of the clinical analysis to ensure better treatment planning, prevent complications, and increase implant success. With the advent of advanced technology, deep learning seems a promising solution towards benefit dental implant procedure. However, the edge borders of dental images are fuzzy in nature which is a major problem and the classical images processing techniques are not much suitable. Even automatic image segmentation is quite challenging task due to complexities associated with dental images including resolution variability, complex and unclear dental structures, poor illumination, random noise, and fuzzy edges borders. newline