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MRI-guided PET reconstruction using a convergent plug-and-play approach

文献类型: 会议论文

第一作者: M. Savanier

作者: M. Savanier 1 ; V. Gautier 2 ; N. J. Pinton 3 ; C. Comtat 1 ; F. Sureau 1 ;

作者机构: 1.BioMaps, Université Paris-Saclay, CEA, CNRS, Inserm, SHFJ, Orsay, France

2.CREATIS, INSA Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, Univ Lyon, Lyon, France

3.LaTIM, INSERM, Université de Bretagne Occidentale, Brest, France

关键词: Microwave integrated circuits;Semiconductor detectors;Magnetic resonance imaging;Resonance;Convex functions;Positron emission tomography;Image reconstruction

会议名称:

主办单位:

页码: 1-1

摘要: Dual modality Positron Emission Tomography (PET)/Magnetic Resonance Imaging (MRI) systems provide seamless hardware-based image coregistration, making MRI-guided PET reconstruction a natural approach. In this work, we investigate the adaptability of the plug-and-play (PnP) paradigm for MRI-guided PET reconstruction. Inspired by proximal optimization algorithms and fixed point theory, the PnP approach proposes to replace the proximity operator of the regularization with a more general denoiser. Precisely, we integrate a deep denoiser - a DRUnet - into the Alternating Direction Method of Multipliers (ADMM) algorithm such that convergence of the iterates to a controlled set of fixed points is ensured. Results on simulated [18F]-FDG PET scans demonstrate that multibranch architectures are more compatible with the PnP framework than multichannel architectures and that the PnP fixed-point solutions have high likelihood and a lower mean squared error than the reconstruction obtained with a classical MRI-guided Bowsher regularization and without MRI guidance.

分类号: r312

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