An efficient fuzzy and morphology based approach to metal artifact reduction from dental CBCT image

New generation image modality which is low radiation dose is highly used in dentistry. In that category, Cone Beam Computed Tomography CBCT are in demand in dental medical application. Due to low radiation dose imaging technique, image reconstruction is prone to artifacts. Artifacts are the discrepancies between the original physical image to the mathematical modelling image process. In dental treatment, mostly metallic filling is done which produces metal artifact in imaging. Which metallic felling produces the reflection effect on imaging that mislead the diagnosis of treatment. Proposed research algorithm which is morphology based reduces the reflection effect of metal artifacts. Metal artifact also effect the visual contrast of CBCT image so that contrast enhancement method is compared which are histogram and fuzzy based method. The output image has been analysed and evaluated using structure of similarity index matrix (SSIM) and peak value ratio in term of Signal versus Noise (PSNR). Visual perception also shows the performance of the proposed work.