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# GliomaGen: Conditional Diffusion for Post-Treatment Glioma MRI Generation
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GliomaGen is a generative diffusion model tailored for synthesizing post-treatment glioma MRI images based on anatomical masks. It leverages a modified **Med-DDPM** architecture to create high-fidelity MRI images conditioned on segmented anatomical features.
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## Model Overview
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| t1n | 58.46 ± 3.86 | 0.0305 ± 0.0011 | 0.7005 ± 0.2585 |
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| t2f | 70.42 ± 4.17 | 0.0370 ± 0.0018 | 0.7842 ± 0.1551 |
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# GliomaGen: Conditional Diffusion for Post-Treatment Glioma MRI Generation
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GliomaGen is a generative diffusion model tailored for synthesizing post-treatment glioma MRI images based on anatomical masks. It leverages a modified **Med-DDPM** architecture to create high-fidelity MRI images conditioned on segmented anatomical features.
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## Model Overview
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| t1n | 58.46 ± 3.86 | 0.0305 ± 0.0011 | 0.7005 ± 0.2585 |
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| t2f | 70.42 ± 4.17 | 0.0370 ± 0.0018 | 0.7842 ± 0.1551 |
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## Usage
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To use GliomaGen for MRI generation, see the [GitHub repository](https://github.com/elijahrenner/gliomagen).
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## BraTS 2024 Adult Post-Treatment Glioma-Synthetic
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Alongisde GliomaGen, a synthetic dataset of $N=2124$ MR images is released on HuggingFace.
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