Generating synthetic past and future states of Knee Osteoarthritis radiographs using Cycle-Consistent Generative Adversarial Neural Networks.

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作者： Fabi,Prezja ^[1] ; Leevi,Annala ^[2] ; Sampsa,Kiiskinen ^[3] ; Suvi,Lahtinen ^[4] ; Timo,Ojala ^[3] ; Paavo,Nieminen ^[3]

作者单位： University of Jyväskylä, Faculty of Information Technology, Jyväskylä, 40014, Finland. Electronic address: faprezja@jyu.fi. ^[1] University of Helsinki, Faculty of Science, Department of Computer Science, Helsinki, Finland; University of Helsinki, Faculty of Agriculture and Forestry, Department of Food and Nutrition, Helsinki, Finland. ^[2] University of Jyväskylä, Faculty of Information Technology, Jyväskylä, 40014, Finland. ^[3] University of Jyväskylä, Faculty of Information Technology, Jyväskylä, 40014, Finland; University of Jyväskylä, Faculty of Mathematics and Science, Department of Biological and Environmental Science, Jyväskylä, 40014, Finland. ^[4]

关键词 Convolutional Neural Network (CNN)CycleGANs Data augmentation Deep Learning DeepFakes Generative Adversarial Networks (GANs)Kellgren–Lawrence Grading (KL Grading)Knee Joint Osteoarthritis (KOA)Prognostic Insights Radiographic (X-ray) Imaging Synthetic Data Generation

DOI 10.1016/j.compbiomed.2025.109785

PMID 39929004

发布时间 2025-02-10

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Computers in biology and medicine

2025年187卷

109785页

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Generating synthetic past and future states of Knee Osteoarthritis radiographs using Cycle-Consistent Generative Adversarial Neural Networks.

Computers in biology and medicine

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Computers in biology and medicine

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Generating synthetic past and future states of Knee Osteoarthritis radiographs using Cycle-Consistent Generative Adversarial Neural Networks.

Computers in biology and medicine

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Computers in biology and medicine

相关期刊

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