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- https://arxiv.org/abs/2105.05318
- 2021
GAN(Generative Adversarial Networks)はますます強力になってきており、複製するように訓練されたデータセットの内容を模倣した、心を揺さぶるようなフォトリアリスティックな画像を生成します。
医用画像の分野では、GANが現実的なRGB画像を生成するのと同様に、実用的な医用データ…
e4exp updated
3 years ago
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Can this model obtain a corresponding 3D model based on MRI or CT data, for example, if the input is human brain MRI, can a 3D brain model be obtained
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Add the GAN from ["Hierarchical Amortized GAN for 3D High Resolution Medical Image Synthesis"](https://ieeexplore.ieee.org/abstract/document/9770375) (official code available in this [link](https://gi…
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# Create Systems Design
## Requirements
## Must Have (Phase I)
* Patient Data Ownership: Patients must be able to share and revoke sharing of any or all data with any provider, on a fine-grai…
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**Suggested format**
- Paper title:
- Author list:
- Paper link:
- Code link:
We have made efforts to include papers related to synthetic tumors as comprehensively as possible, but we acknowled…
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# Abstract
Generative Adversarial Networks(GAN)은 데이터 생성에서 뛰어난 모습을 보이고 있다. 많은 영역에서 쓰이고 있지만 여전히 안정적인 학습에는 어려움이 따른다. 문제점으로는 Nash-equilibrium, internal covariate shift, mode collapse, vanishing gradient,…
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Here are a few things I found related to the use of the generative models to obtain synthetic medical data.
## Bibliography
- **Synthesis in Multi-Contrast MRI with Conditional Generative Adver…
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+1. Gatys, Leon, Alexander S. Ecker, and Matthias Bethge. "Texture synthesis using convolutional neural networks." Advances in Neural Information Processing Systems. 2015.
+2. Gatys, Leon A., Alexa…
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Hi,
Please consider including our recent work, I2I-Mamba, in your collection. Here are the links to the preprint and the GitHub repository:
ArXiv preprint: https://arxiv.org/abs/2405.14022
GitH…