[Style Transfer]Generative Adversarial Network in Medical Imaging: A Review
Generative Adversarial Network in Medical Imaging: A Review 医学图像中生成对抗网络的研究进展-综述 Abstract 得益于生成对抗网络可以隐式的完成数据分布的建模，因此在计算机视觉下的众多任务中大放异彩。生成器会生成大量样本，判别器会对大量未标注的样本进行类别预测，因此GAN已在域迁移、分割任务、分类任务、跨模态合成等领域做了诸多探索。
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相关文章
- 1. GAN在医学图像综述——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. [阅读笔记]Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and C
- 6. "A Review of Medical Image Classification Techniques-2011"笔记
- 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