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Found 2 papers, 1 papers with code
Iterative-in-Iterative Super-Resolution Biomedical Imaging Using One Real Image
Deep learning-based super-resolution models have the potential to revolutionize biomedical imaging and diagnoses by effectively tackling various challenges associated with early detection, personalized medicine, and clinical automation.
Self-similarity-based super-resolution of photoacoustic angiography from hand-drawn doodles
To address this challenge, we propose a novel approach that employs a super-resolution PAA method trained with forged PAA images.
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