Simin Mirzaei;Hamid Reza Tohidypour;Panos Nasiopoulos;Siddharth R. Vora;Shahriar Mirabbasi
{"title":"An Advanced Denoising Technique for Low-Dose CBCT Imaging: Enhancing Image Quality and Consumer Safety in Dental Diagnostics","authors":"Simin Mirzaei;Hamid Reza Tohidypour;Panos Nasiopoulos;Siddharth R. Vora;Shahriar Mirabbasi","doi":"10.1109/TCE.2025.3535668","DOIUrl":null,"url":null,"abstract":"Cone Beam Computed Tomography (CBCT) plays a crucial role in dentistry, providing detailed imaging for diagnosis and treatment planning. However, standard CBCT imaging involves high radiation levels, raising safety concerns and driving the adoption of low-dose imaging, which often compromises image quality. This paper presents a novel denoising pipeline specifically designed to address the complex noise characteristics of low-dose CBCT images, which we have identified as resembling speckle noise. Our approach integrates advanced filtering techniques, innovative noise estimation methods, and brightness correction for 3D image reconstruction, while also leveraging the human visual system’s sensitivity to different frequencies to enhance CBCT visual quality. Experimental results demonstrate that our method outperforms state-of-the-art denoising techniques, including deep learning-based approaches, in achieving superior visual quality. This innovation not only enhances diagnostic precision but also improves patient safety, setting a new benchmark for image quality in dental care.","PeriodicalId":13208,"journal":{"name":"IEEE Transactions on Consumer Electronics","volume":"71 1","pages":"796-807"},"PeriodicalIF":4.3000,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Consumer Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10856267/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Cone Beam Computed Tomography (CBCT) plays a crucial role in dentistry, providing detailed imaging for diagnosis and treatment planning. However, standard CBCT imaging involves high radiation levels, raising safety concerns and driving the adoption of low-dose imaging, which often compromises image quality. This paper presents a novel denoising pipeline specifically designed to address the complex noise characteristics of low-dose CBCT images, which we have identified as resembling speckle noise. Our approach integrates advanced filtering techniques, innovative noise estimation methods, and brightness correction for 3D image reconstruction, while also leveraging the human visual system’s sensitivity to different frequencies to enhance CBCT visual quality. Experimental results demonstrate that our method outperforms state-of-the-art denoising techniques, including deep learning-based approaches, in achieving superior visual quality. This innovation not only enhances diagnostic precision but also improves patient safety, setting a new benchmark for image quality in dental care.
期刊介绍:
The main focus for the IEEE Transactions on Consumer Electronics is the engineering and research aspects of the theory, design, construction, manufacture or end use of mass market electronics, systems, software and services for consumers.