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

2017 International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2017-05-01 DOI:10.1109/CCAA.2017.8229985

Anita Thakur, Vishu Pargain, Pratul Singh, S. Chauhan, P. Khare, Prashant Mor

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引用次数: 3

Abstract

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.

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一种有效的基于模糊和形态学的牙齿CBCT图像金属伪影还原方法

低辐射剂量的新一代成像技术在牙科领域得到了广泛应用。其中，锥形束计算机断层扫描(CBCT)在牙科医学领域的应用需求较大。由于低辐射剂量成像技术，图像重建容易产生伪影。伪影是原始物理图像与数学建模图像之间的差异。在牙科治疗中，多采用金属充填，在成像中产生金属伪影。其中金属屑对影像产生反射作用，误导诊断治疗。提出了一种基于形态学的减小金属伪影反射效应的研究算法。金属伪影也会影响CBCT图像的视觉对比度，因此比较了直方图增强和模糊增强两种增强方法。利用相似指数矩阵(SSIM)结构和峰值比的信噪比(PSNR)对输出图像进行分析和评价。视觉感知也显示了所提出的工作的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2017 International Conference on Computing, Communication and Automation (ICCCA)

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