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Generative Models Improve Radiomics Performance in Different Tasks and
  Different Datasets: An Experimental Study

Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study

6 September 2021
Junhua Chen
Inigo Bermejo
Andre Dekker
L. Wee
    DiffM
    MedIm
    AI4CE
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Papers citing "Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study"

2 / 2 papers shown
Title
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance
  Learning and Radiomics
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics
Junhua Chen
H. Zeng
Chong Zhang
Zhenwei Shi
Andre Dekker
L. Wee
Inigo Bermejo
31
25
0
29 Apr 2021
Low Dose CT Image Denoising Using a Generative Adversarial Network with
  Wasserstein Distance and Perceptual Loss
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss
Qingsong Yang
Pingkun Yan
Yanbo Zhang
Hengyong Yu
Yongyi Shi
X. Mou
Mannudeep K. Kalra
Ge Wang
GAN
MedIm
55
1,193
0
03 Aug 2017
1