A Fast and Accurate Dental Micro-Ct Image Denoising Based on Total Variation Modeling Publisher



Lashgari M¹ ; Rabbani H^{1, 2} ; Shahmorad M³ ; Swain M³
Source: IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation Published:2015

Abstract

Quantitative evaluation of mineral density of carious dental lesion is one of the major aims in cariology investigations particularly in the study of caries remineralization. Nowadays X-ray micro computed tomography (Micro-CT) is used as a well-known modality for this purpose. However, the produced Micro-CT images are affected by substantial noise. To address this issue, we propose a new approach for de-noising dental Micro-CT images based on total variation (TV) modeling. The idea of applying this method traces back to the structural features of a tooth, and almost non-textural nature of noise-free images. So, using TV we intend to separate texture from cartoon which results in major reduction of the noise in Micro-CT dental images. Our simulation results on a dataset of 51 teeth of size 1000×1000 showed that our method outperforms BM3D method, currently one of the state-of-the-art de-noising methods, in terms of Contrast-to-Noise Ratio (123.02±11.29 vs. 96.79±6.87) while Edge Preservation Indexes are the same. © 2015 IEEE.