ShanghaiTech University Knowledge Management System
| Parallel Sinogram and Image Framework With Co-Training Strategy for Metal Artifact Reduction in Tooth Ct Images | |
| 2022 | |
| 会议录名称 | PROCEEDINGS - INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING |
| ISSN | 1945-7928 |
| 卷号 | 2022-March |
| 发表状态 | 已发表 |
| DOI | 10.1109/ISBI52829.2022.9761653 |
| 摘要 | Computed Tomography (CT) is widely used in oral treatment planning but metal artifacts caused by high-density materials such as metal implants heavily influence the effectivness of digital tooth models. In existing studies on metal artifact reduction (MAR), the mathematical relationship between the spatial and projection domains is generally sequentially considered, or metal traces/masks are required as priors. In this paper, we propose a parallel sinogram and image framework (PSIF), aiming to enable MAR in the spatial and projection domains to benefit each other. We formulate this task as an image enhancement problem in the spatial domain and a sinogram completion problem in the projection domain using two parallel networks, and propose a co-training strategy with forward-backward projection consistency loss to optimize the model. The experimental results on 10, 000 tooth slices demonstrate that our proposed method can effectively recover tooth outlines and suppress the stripe artifacts. © 2022 IEEE. |
| 会议录编者/会议主办者 | IEEE Engineering in Medicine and Biology Society (EMBS) ; IEEE Signal Processing Society ; Institute of Electrical and Electronic Engineers (IEEE) |
| 关键词 | Computerized tomography Medical imaging Metals Backward projection Co-training Computed tomography images Cotraining strategy Forward-backward projection consistency Metal artifact reduction Projection domain Sinograms Spatial domains Training strategy |
| 会议名称 | 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 |
| 出版地 | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| 会议地点 | Kolkata, India |
| 会议日期 | March 28, 2022 - March 31, 2022 |
| URL | 查看原文 |
| 收录类别 | EI ; CPCI ; CPCI-S |
| 语种 | 英语 |
| 资助项目 | National Natural Science Foundation of China[62131015] ; Science and Technology Commission of Shanghai Municipality (STCSM)[21010502600] ; Key R&D Program of Guang-dong Province, China[2021B0101420006] ; China Postdoctoral Science Foundation[ |
| WOS研究方向 | Engineering ; Radiology, Nuclear Medicine & Medical Imaging |
| WOS类目 | Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging |
| WOS记录号 | WOS:000836243800250 |
| 出版者 | IEEE Computer Society |
| EI入藏号 | 20221912089256 |
| EI主题词 | Image enhancement |
| EISSN | 1945-8452 |
| EI分类号 | 461.1 Biomedical Engineering ; 723.5 Computer Applications ; 746 Imaging Techniques |
| 原始文献类型 | Conference article (CA) |
| 来源库 | IEEE |
| 引用统计 | 正在获取...
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| 文献类型 | 会议论文 |
| 条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/180960 |
| 专题 | 生物医学工程学院_PI研究组_沈定刚组 信息科学与技术学院_博士生 生物医学工程学院_PI研究组_崔智铭组 |
| 通讯作者 | Song, Yang |
| 作者单位 | 1.Univ New South Wales, Sch Comp Sci & Engn, Sydney, NSW, Australia 2.ShanghaiTech Univ, Sch Biomed Engn, Shanghai, Peoples R China 3.Shanghai United Imaging Intelligence Co Ltd, Shanghai, Peoples R China 4.Chongqing Univ Posts & Telecommun, Chongqing, Peoples R China 5.Affiliated Hangzhou First People Hosp, Dept Radiol, Hangzhou, Peoples R China 6.Shanghai Ninth Peoples Hosp, Shanghai, Peoples R China |
| 第一作者单位 | 生物医学工程学院 |
| 推荐引用方式 GB/T 7714 | Hu, Yan,Pan, Yongsheng,Song, Yang,et al. Parallel Sinogram and Image Framework With Co-Training Strategy for Metal Artifact Reduction in Tooth Ct Images[C]//IEEE Engineering in Medicine and Biology Society (EMBS), IEEE Signal Processing Society, Institute of Electrical and Electronic Engineers (IEEE). 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE Computer Society,2022. |
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