Example-Based Super-Resolution Image Reconstruction for Positron Emission Tomography Using Sparse Coding

This paper presents example-based methods for super-resolution (SR) reconstruction from a single set of low-resolution projections (or a sinogram) in positron emission tomography (PET). While deep learning-based SR approaches have shown promise across various imaging modalities, their application in...

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Hlavní autoři:	Xue Ren, Soo-Jin Lee
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2024-01-01
Edice:	IEEE Access
Témata:	Image reconstruction super-resolution sparse coding penalized-likelihood methods inverse problems positron emission tomography
On-line přístup:	https://ieeexplore.ieee.org/document/10772437/
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