[Style Transfer]Generative Adversarial Network in Medical Imaging: A Review
Generative Adversarial Network in Medical Imaging: A Review 醫學圖像中生成對抗網絡的研究進展-綜述 Abstract 得益於生成對抗網絡可以隱式的完成數據分佈的建模，因此在計算機視覺下的衆多任務中大放異彩。生成器會生成大量樣本，判別器會對大量未標註的樣本進行類別預測，因此GAN已在域遷移、分割任務、分類任務、跨模態合成等領域做了諸多探索。
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相關文章
- 1. GAN在醫學圖像綜述——Generative adversarial network in medical imaging: A review
- 2. 01_kaggle - Using a 3D Convolutional Neural Network on medical imaging data (CT Scans) for Kaggle
- 3. [Style Transfer]——Neural Style Transfer: A Review
- 4. Paper Review: Adversarial Examples
- 5. [閱讀筆記]Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and C
- 6. "A Review of Medical Image Classification Techniques-2011"筆記
- 7. On the Automatic Generation of Medical Imaging Reports
- 8. [Style Transfer]——GANs for Medical Image Analysis
- 9. [Style Transfer]——A Style-Based Generator Architecture for Generative Adversarial Networks
- 10. Graph Neural Network Review