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Transformer-based Models for Unsupervised Anomaly Segmentation in Brain MR Images

License: GNU General Public License v3.0

Python 43.06% Jupyter Notebook 56.94%
deep-learning deep-neural-networks autoencoders latent-variable-models transformers unsupervised-deep-learning anomaly-detection-models flair mri-brain reconstruction

transformers_unsupervised_anomaly_segmentation's Introduction

👋 Hi, I’m AHMED,
💻 AI research scientist specialized in computer vision at FX-Conseil - école polytechnique, FRANCE.
📚 Hailing from STEM background with validated experience in data science and artificial intelligence projects for research and industrial applications.
🌱 Currently working on latent diffusion models (LDMs) for conditional image generation.
🤝 Looking to collaborate on healthcare projects.
📫 How to reach me: https://www.linkedin.com/in/ahmed-ghorbel97/

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transformers_unsupervised_anomaly_segmentation's Issues

How to find the data?

Congratulations for your work. I'm trying to reproduce this work but I cannot find the drive files follow the data.txt, could you please check it?

VQ-VAE with TF

Just wondering if the code of "VQ-VAE + Transformer" in your paper has been uploaded. Is it H_TAE.py or anything else? Thanks!

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