Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Content-Noise Feature Fusion Neural Network for Image Denoising in Magnetic Particle Imaging | |
Tan Wang1,2,3![]() ![]() ![]() ![]() | |
2023 | |
会议名称 | IEEE Engineering in Medicine and Biology Conference |
会议日期 | 2023 |
会议地点 | Sydney Australia |
出版者 | IEEE |
摘要 | Magnetic particle imaging (MPI) is a tomographic imaging method that quantitatively determines the distribution of magnetic nanoparticles (MNPs). However, the performance of MPI is primarily limited by the noise in the receive coil and electronic devices, which causes quantification errors for MPI images. Existing methods cannot efficiently eliminate noise while preserve structural details in MPI images. To address this problem, we propose a Content-Noise Feature Fusion Neural Network equipped with tailored modules of noise learning and content learning. It can simultaneously learn content and noise features of raw MPI images. Experimental results show that the proposed method outperforms the state-of-the-art methods on structural details preservation and image noise reduction of different levels. |
收录类别 | EI |
七大方向——子方向分类 | 医学影像处理与分析 |
国重实验室规划方向分类 | AI For Science |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57480 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Hui Hui |
作者单位 | 1.CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Beijing Key Laboratory of Molecular Imaging 4.School of Computer Science and Engineering, Southeast University 5.Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People’s Republic of China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Tan Wang,Liwen Zhang,Zechen Wei,et al. Content-Noise Feature Fusion Neural Network for Image Denoising in Magnetic Particle Imaging[C]:IEEE,2023. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
王探EMBC.pdf(1180KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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