Zero-Shot Recon2Recon: Data-Free Unsupervised Denoiser Learning for Plug-and-Play Magnetic Resonance Imaging Reconstruction

This work presents a novel zero-shot learning method for undersampled magnetic resonance imaging (MRI) reconstruction. The proposed method utilizes a plug-and-play approach, wherein the denoiser neural network, serving as the image prior, is trained solely with the single acquired undersampled k-spa...

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Bibliographic Details
Main Author: Tae Hyung Kim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10933922/
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