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Background: Deep learning-based super-resolution (SR) algorithms aim to reconstruct low-resolution (LR) images into high-fidelity high-resolution (HR) ...
The novel proposed SR strategy for medical images performs efficient reconstruction at arbitrary resolution, marking a significant breakthrough in the field ...
Apr 17, 2024 · In this work we propose a modified NLM approach. NLM approach exploit redundancy in images. We have considered the basic NLM algorithm, where, ...
Neighborhood evaluator for efficient super-resolution reconstruction of 2D medical images. ... efficient super-resolution reconstruction of 2D medical images ...
Neighborhood evaluator for efficient super-resolution reconstruction of 2D medical images ... Ren, Towards efficient medical lesion image super-resolution ...
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Feb 28, 2024 · Deep learning-based super-resolution (SR) algorithms aim to reconstruct low-resolution (LR) images into high-fidelity high-resolution (HR) ...
Feb 25, 2024 · Neighborhood evaluator for efficient super-resolution reconstruction of 2D medical images ... resolution medical images into high-resolution ...
4 days ago · Diffusion Models for Memory-efficient Processing of 3D Medical Images ... Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using ...
Neighborhood evaluator for efficient super-resolution reconstruction of 2D medical images. ... high-quality reconstruction of LR digital medical images. M ...