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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language: en
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+ tags:
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+ - diffusion-models
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+ - medical-imaging
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+ - glioma
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+ - synthetic-data
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+ - MRI
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+ license: mit
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+ datasets:
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+ - BraTS2024
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+ model-index:
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+ - name: GliomaGen
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+ results:
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+ - task:
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+ type: image-generation
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+ dataset:
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+ name: BraTS2024 Adult Post-Treatment Glioma
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+ type: medical-imaging
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+ metrics:
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+ - name: FID (t1c)
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+ type: frechet-inception-distance
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+ value: 55.2028 ± 3.7446
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+ - name: FID (t2w)
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+ type: frechet-inception-distance
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+ value: 54.9974 ± 3.2271
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+ - name: KID (t1c)
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+ type: kernel-inception-distance
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+ value: 0.0293 ± 0.0019
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+ - name: MS-SSIM (t1c)
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+ type: multi-scale-structural-similarity
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+ value: 0.7647 ± 0.2106
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+ ---
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+
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+ # GliomaGen: Conditional Diffusion for Post-Treatment Glioma MRI Generation
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+
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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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+
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+ ## Model Overview
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+ GliomaGen aims to address data scarcity in post-treatment glioma segmentation tasks by expanding existing datasets with synthetic, high-quality MRI volumes. The model takes anatomical masks as input and generates multi-modal MRI scans conditioned on segmentation labels.
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+
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+ ## Model Performance
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+ ### **Quantitative Metrics**
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+ | Modality | FID (↓) | KID (↓) | MS-SSIM (↑) |
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+ |----------|--------|--------|-------------|
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+ | t1c | 55.20 ± 3.74 | 0.0293 ± 0.0019 | 0.7647 ± 0.2106 |
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+ | t2w | 54.99 ± 3.23 | 0.0291 ± 0.0010 | 0.6513 ± 0.2881 |
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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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+
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+ ## Usage
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+ ### **Loading the Model**
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+ To use GliomaGen for MRI generation, see the [GitHub repository](https://github.com/elijahrenner/gliomagen).