Metal Artefact Reduction from Dental CBCT Image Using Morphology and Fuzzy Logic

Cone beam computed tomography (CBCT) is a new-generation 3D image modality which is highly used in dentistry. As CBCT is a low-radiation imaging technique, reconstruction of image is prone to artefacts. Artefacts are the discrepancies between the original physical image and the mathematical modelling image process. In dental treatment, mostly metallic filling is done which produces metal artefact in imaging, in which it produces the reflection effect on imaging that misleads the diagnosis of treatment. In this paper, the proposed method reduces the reflection effect of metal artefacts and enhances the contrast of CBCT image. Here the proposed technique used morphological approach for reflection reduction, and fuzzy enhancement is used for contrast improvement. The output image has been analysed and evaluated using structure of similarity index matrix (SSIM) and peak value ratio in terms of signal versus noise (PSNR). Visual perception also shows the performance of the proposed work.