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Medical image super-resolution reconstruction algorithms based on deep learning: A survey
Computer Methods and Programs in Biomedicine, 2023BACKGROUND AND OBJECTIVE With the high-resolution (HR) requirements of medical images in clinical practice, super-resolution (SR) reconstruction algorithms based on low-resolution (LR) medical images have become a research hotspot.
Defu Qiu, Xuesong Wang
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Image super-resolution reconstruction based on feature map attention mechanism
Applied Intelligence, 2021Yuantao Chen, Ke Gu, Runlong Xia
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Remote Sensing, 2022 In recent years, more and more researchers have used deep learning methods for super-resolution reconstruction and have made good progress. However, most of the existing super-resolution reconstruction models generate low-resolution images for training ...
Mingqiang Guo, Zeyuan Zhang
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Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI.
Radiology, 2023Background Deep learning (DL) reconstructions can enhance image quality while decreasing MRI acquisition time. However, DL reconstruction methods combined with compressed sensing for prostate MRI have not been well studied.
Leon M Bischoff +12 more
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The Physics of Fluids, 2023
Recent attempts to employ deep learning technology for the super-resolution (SR) reconstruction of turbulence have focused chiefly on reconstructing two-dimensional (2D) slices of the three-dimensional (3D) flow fields.
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Recent attempts to employ deep learning technology for the super-resolution (SR) reconstruction of turbulence have focused chiefly on reconstructing two-dimensional (2D) slices of the three-dimensional (3D) flow fields.
semanticscholar +1 more source
Super-resolution reconstruction of turbulent flows with a transformer-based deep learning framework
The Physics of Fluids, 2023Details of flow field are highly relevant to understand the mechanism of turbulence, but obtaining high-resolution turbulence often requires enormous computing resources.
Qin Xu +3 more
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Learning Super-Resolution Reconstruction for High Temporal Resolution Spike Stream
IEEE transactions on circuits and systems for video technology (Print), 2023Spike camera is a new type of bio-inspired vision sensor, each pixel of which perceives the brightness of the scene independently, and finally outputs 3-dimensional spatiotemporal spike streams.
Xijie Xiang +5 more
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D2UNet: Dual Decoder U-Net for Seismic Image Super-Resolution Reconstruction
IEEE Transactions on Geoscience and Remote Sensing, 2023Super-resolution reconstruction is an essential task of seismic inversion due to the low resolution and strong noise of field data. Popular deep networks derived from U-Net lack the ability to recover detailed edge features and weak signals.
Fan Min +3 more
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MGDUN: An interpretable network for multi-contrast MRI image super-resolution reconstruction
Comput. Biol. Medicine, 2023Magnetic resonance imaging (MRI) Super-Resolution (SR) aims to obtain high resolution (HR) images with more detailed information for precise diagnosis and quantitative image analysis.
Gang Yang +5 more
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Super-resolution reconstruction of hyperspectral images
IEEE Transactions on Image Processing, 2005Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images.
Toygar Akgun +2 more
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