2024
DOI: 10.3390/info15100655
|View full text |Cite
|
Sign up to set email alerts
|

MRI Super-Resolution Analysis via MRISR: Deep Learning for Low-Field Imaging

Yunhe Li,
Mei Yang,
Tao Bian
et al.

Abstract: This paper presents a novel MRI super-resolution analysis model, MRISR. Through the utilization of generative adversarial networks for the estimation of degradation kernels and the injection of noise, we have constructed a comprehensive dataset of high-quality paired high- and low-resolution MRI images. The MRISR model seamlessly integrates VMamba and Transformer technologies, demonstrating superior performance across various no-reference image quality assessment metrics compared with existing methodologies. I… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 35 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?