دورية أكاديمية

A new dental CBCT metal artifact reduction method based on a dual-domain processing framework

التفاصيل البيبلوغرافية
العنوان: A new dental CBCT metal artifact reduction method based on a dual-domain processing framework
المؤلفون: Tang, Hui, Lin, Yu Bing, Jiang, Su Dong, Li, Yu, Li, Tian, Bao, Xu Dong
المصدر: Physics in Medicine & Biology ; volume 68, issue 17, page 175016 ; ISSN 0031-9155 1361-6560
بيانات النشر: IOP Publishing
سنة النشر: 2023
الوصف: Objective. Cone beam computed tomography (CBCT) has been wildly used in clinical treatment of dental diseases. However, patients often have metallic implants in mouth, which will lead to severe metal artifacts in the reconstructed images. To reduce metal artifacts in dental CBCT images, which have a larger amount of data and a limited field of view compared to computed tomography images, a new dental CBCT metal artifact reduction method based on a projection correction and a convolutional neural network (CNN) based image post-processing model is proposed in this paper . Approach. The proposed method consists of three stages: (1) volume reconstruction and metal segmentation in the image domain, using the forward projection to get the metal masks in the projection domain; (2) linear interpolation in the projection domain and reconstruction to build a linear interpolation (LI) corrected volume; (3) take the LI corrected volume as prior and perform the prior based beam hardening correction in the projection domain, and (4) combine the constructed projection corrected volume and LI-volume slice-by-slice in the image domain by two concatenated U-Net based models (CNN1 and CNN2). Simulated and clinical dental CBCT cases are used to evaluate the proposed method. The normalized root means square difference (NRMSD) and the structural similarity index (SSIM) are used for the quantitative evaluation of the method. Main results. The proposed method outperforms the frequency domain fusion method (FS-MAR) and a state-of-art CNN based method on the simulated dataset and yields the best NRMSD and SSIM of 4.0196 and 0.9924, respectively. Visual results on both simulated and clinical images also illustrate that the proposed method can effectively reduce metal artifacts. Significance . This study demonstrated that the proposed dual-domain processing framework is suitable for metal artifact reduction in dental CBCT images.
نوع الوثيقة: article in journal/newspaper
اللغة: unknown
DOI: 10.1088/1361-6560/acec29
DOI: 10.1088/1361-6560/acec29/pdf
الإتاحة: https://doi.org/10.1088/1361-6560/acec29Test
حقوق: https://iopscience.iop.org/page/copyrightTest ; https://iopscience.iop.org/info/page/text-and-data-miningTest
رقم الانضمام: edsbas.3F8720A8
قاعدة البيانات: BASE