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How Can We Make GAN Perform Better in Single Medical Image
  Super-Resolution? A Lesion Focused Multi-Scale Approach

How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach

10 January 2019
Jin Zhu
Guang Yang
Pietro Lió
    GAN
    MedIm
ArXivPDFHTML

Papers citing "How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach"

3 / 3 papers shown
Title
A residual dense vision transformer for medical image super-resolution
  with segmentation-based perceptual loss fine-tuning
A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuning
Jin Zhu
Guang Yang
Pietro Lio'
ViT
MedIm
32
5
0
22 Feb 2023
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance
  Imaging -- Mini Review, Comparison and Perspectives
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging -- Mini Review, Comparison and Perspectives
Guang Yang
Jun Lv
Yutong Chen
Jiahao Huang
Jin Zhu
MedIm
26
9
0
04 May 2021
QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative
  Adversarial Networks with Increased Receptive Field
QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with Increased Receptive Field
Yicheng Chen
A. Jakary
Sivakami Avadiappan
Christopher P. Hess
J. Lupo
MedIm
18
60
0
08 May 2019
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