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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Awesome GAN for Medical Imaging
| Date | Stars |
|---|---|
| 2026-07-24 | 2363 |
| 2026-07-25 | 2363 |
| 2026-07-28 | 2363 |
| 2026-07-30 | 2363 |
| 2026-08-06 | 2363 |
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# Awesome GAN for Medical Imaging A curated list of awesome GAN resources in medical imaging, inspired by the other awesome-* initiatives. For a complete list of GANs in general computer vision, please visit [really-awesome-gan](https://github.com/nightrome/really-awesome-gan). To complement or correct it, please contact me at [email protected] or send a pull request. ## Overview - [Review](#review) - [Low Dose CT Denoising](#low-dose-ct-denoising) - [Segmentation](#segmentation) - [Detection](#detection) - [Medical Image Synthesis](#medical-image-synthesis) - [Reconstruction](#reconstruction) - [Classification](#classification) - [Registration](#registration) - [Others](#others) # Review - [Generative Adversarial Network in Medical Imaging: A Review] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=Generative+adversarial+network+in+medical+imaging%3A+A+review&btnG=) [[MedIA]](https://www.sciencedirect.com/science/article/abs/pii/S1361841518308430) - [GANs for Medical Image Analysis] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=GANs+for+Medical+Image+Analysis&btnG=) [[arXiv]](https://arxiv.org/abs/1809.06222) - [Generative adversarial networks and adversarial methods in biomedical image analysis] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=Generative+adversarial+networks+and+adversarial+methods+in+biomedical+image+analysis&btnG=) [[arXiv]](https://arxiv.org/abs/1810.10352) # Low Dose CT Denoising - [Generative Adversarial Networks for Noise Reduction in Low-Dose CT] [[scholar]](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&sciodt=0%2C5&cites=18303813038948630123&scipsc=&q=Generative+Adversarial+Networks+for+Noise+Reduction+in+Low-Dose+CT&btnG=) [[TMI]](http://ieeexplore.ieee.org/document/7934380/) - [Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss] [[scholar]](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Low+Dose+CT+Image+Denoising+Using+a+Generative+Adversarial+Network+with+Wasserstein+Distance+and+Perceptual+Loss&btnG=) [[arXiv]](https://arxiv.org/abs/1708.00961) - [Sharpness-aware Low dose CT denoising using conditional generative adversarial network] [[scholar]](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Sharpness-aware+Low+dose+CT+denoising+using+conditional+generative+adversarial+network&btnG=) [[arXiv]](https://arxiv.org/abs/1708.06453) [[JDI]](https://link.springer.com/article/10.1007/s10278-018-0056-0) [[code]](https://github.com/xinario/SAGAN) - [Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=Cycle+Consistent+Adversarial+Denoising+Network+for+Multiphase+Coronary+CT+Angiography&btnG=) [[arXiv]](https://arxiv.org/abs/1806.09748) - [Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising] [[scholar]](https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&q=Structure-sensitive+Multi-scale+Deep+Neural+Network+for+Low-Dose+CT+Denoising&btnG=) [[arXiv]](https://arxiv.org/abs/1805.00587) - [3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network] [[scholar]](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=3-D+Convolutional+Encoder-Decoder+Network+for+Low-Dose+CT+via+Transfer+Learning+From+a+2-D+Trained+Network&btnG=) [[arXiv]](https://arxiv.org/abs/1802.05656) - [CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement] [[scholar]](https://scholar.google.ca/scholar?q=CT+Image+Enhancement+Using+Stacked+Generative+Adversarial+Networks+and+Transfer+Learning+for+Lesion+Segmentation+Improvement&hl=en&as_sdt=0&as_vis=1&oi=scholart) [[MLMI2018]](https://link.springer.com/chapter/10.1007/978-3-030-00919-9_6) - [TomoGAN: Low-Dose X-Ray Tomography with Generative Adversarial Networks] [[scholar]](https://scholar.google.
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Alex Bailo · Netherlands
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:91b69c2ff13cf896, topic:super-resolution, topic:gan
matched fp:91b69c2ff13cf896, name:medical imaging, desc:medical imaging, readme:medical imaging