Image Denoising of Low-Dose PET Mouse Scans with Deep Learning: Validation Study for Preclinical Imaging Applicability.

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作者： Florence M,Muller ^[1] ; Boris,Vervenne ^[2] ; Jens,Maebe ^[3] ; Eric,Blankemeyer ^[3] ; Mark A,Sellmyer ^[4] ; Rong,Zhou ^[4] ; Joel S,Karp ^[4] ; Christian,Vanhove ^[4] ; Stefaan,Vandenberghe ^[3]

作者单位： Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium. FlorenceMarie.Muller@UGent.be. ^[1] Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA. FlorenceMarie.Muller@UGent.be. ^[2] Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium. ^[3] Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA. ^[4]

关键词 Convolutional neural networks Deep learning Image denoising Low-dose imaging Micro-PET

主题词动物(Animals);小鼠(Mice);正电子发射断层显像术(Positron-Emission Tomography);氟脱氧葡萄糖F18(Fluorodeoxyglucose F18);算法(Algorithms);体模, 显象术(Phantoms, Imaging);图像处理, 计算机辅助(Image Processing, Computer-Assisted)

DOI 10.1007/s11307-023-01866-x

PMID 37875748

发布时间 2024-02-01

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