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  ---
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  # PRLx-GAN
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  Repository for [_Synthetic Generation and Latent Projection Denoising of Rim Lesions in Multiple Sclerosis_](https://openreview.net/forum?id=wFkiqB5spT&referrer=%5Bthe%20profile%20of%20Alexandra%20Grace%20Roberts%5D(%2Fprofile%3Fid%3D~Alexandra_Grace_Roberts1)) published in [Synthetic Data](https://syndata4cv.github.io/) at [CVPR 2025](https://cvpr.thecvf.com/).
 
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  ## Summary
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- Paramagnetic rim lesions (PRLs) are a rare but highly prognostic lesion subtype in multiple sclerosis, visible only on susceptibility ($\chi$) contrasts. This work presents a generative framework to: <br/>
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  * Synthesize new rim lesion maps that address class imbalance in training data <br/>
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  * Enable a novel denoising method to resolve radiologist disagreements on noisy labels, "ambiguous rim lesions". <br/>
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- <br/>
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- <br/>
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  <div style="width:50%; margin: auto;">
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  ![image/gif](https://cdn-uploads.huggingface.co/production/uploads/6839b01245636acda0a9edea/nawkDQNtgB8Ms9F1y0-Cg.gif)
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  <i>Latent projection iterations to identify the denoised rim lesion from a "noisy" rim lesion.</i>
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  </div>
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- <br/>
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  ## Contents
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  Uncurated synthetic rim lesion susceptibilities can be found in [`png`](https://github.com/agr78/PRLx-GAN/tree/main/png) <br/>
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  ```
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  cd ./out
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # PRLx-GAN
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  Repository for [_Synthetic Generation and Latent Projection Denoising of Rim Lesions in Multiple Sclerosis_](https://openreview.net/forum?id=wFkiqB5spT&referrer=%5Bthe%20profile%20of%20Alexandra%20Grace%20Roberts%5D(%2Fprofile%3Fid%3D~Alexandra_Grace_Roberts1)) published in [Synthetic Data](https://syndata4cv.github.io/) at [CVPR 2025](https://cvpr.thecvf.com/).
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+
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  ## Summary
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+ Paramagnetic rim lesions (PRLs) are a rare but highly prognostic lesion subtype in multiple sclerosis, visible only on susceptibility ($\chi$) contrasts. [This work](https://huggingface.co/papers/2505.23353) presents a generative framework to: <br/>
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  * Synthesize new rim lesion maps that address class imbalance in training data <br/>
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  * Enable a novel denoising method to resolve radiologist disagreements on noisy labels, "ambiguous rim lesions". <br/>
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  <div style="width:50%; margin: auto;">
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  ![image/gif](https://cdn-uploads.huggingface.co/production/uploads/6839b01245636acda0a9edea/nawkDQNtgB8Ms9F1y0-Cg.gif)
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  <i>Latent projection iterations to identify the denoised rim lesion from a "noisy" rim lesion.</i>
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  </div>
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+
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  ## Contents
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  Uncurated synthetic rim lesion susceptibilities can be found in [`png`](https://github.com/agr78/PRLx-GAN/tree/main/png) <br/>
 
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  ```
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  cd ./out
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  ```
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+
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+ ## Publications
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+ If this code is used, please cite the following:
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+ > [Conference Paper](https://openreview.net/forum?id=wFkiqB5spT&noteId=wFkiqB5spT): A. G. Roberts et al., "Synthetic Generation and Latent Projection Denoising of Rim Lesions in Multiple Sclerosis," Synthetic Data for Computer Vision at CVPR, 2025.
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+ >
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+
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+ ## BibTex
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+ ```bibtex
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+ @inproceedings{
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+ roberts2025synthetic,
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+ title={Synthetic Generation and Latent Projection Denoising of Rim Lesions in Multiple Sclerosis},
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+ author={Alexandra Grace Roberts and Ha Manh Luu and Mert Sisman and Alexey V. Dimov and Ceren Tozlu and Ilhami Kovanlikaya and Susan Gauthier and Thanh D. Nguyen and Yi Wang},
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+ booktitle={Synthetic Data for Computer Vision Workshop @ CVPR 2025},
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+ year={2025},
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+ url={https://openreview.net/forum?id=wFkiqB5spT}
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+ }
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+ ```
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+
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+ ## Acknowledgements
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+ This method relies on the [StyleGAN2-ADA](https://github.com/NVlabs/stylegan2-ada-pytorch) architecture developed by [`@tkarras`](https://github.com/tkarras).
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+ ## Contact
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+ Please direct questions to [Alexandra Roberts](https://github.com/agr78) at agr78@cornell.edu.
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+