GabrieleLozupone/LDAE
Official PyTorch implementation of "Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging". LDAE is a novel unsupervised framework for 3D medical imaging that combines a latent diffusion model with semantic controls.
This tool helps medical researchers and clinicians analyze 3D brain MRI scans more effectively. It takes raw or preprocessed MRI images and can generate modified scans that show how a brain might look with different clinical traits, like Alzheimer's progression, or create variations of a scan while preserving core anatomy. This is designed for scientists or medical professionals working with brain imaging data, especially those studying neurodegenerative diseases.
Use this if you need to understand, manipulate, or simulate changes in 3D brain MRI scans, particularly for studying disease progression or generating diverse synthetic data for research.
Not ideal if you are looking for a straightforward diagnostic tool or simply need to view and annotate medical images without advanced generative or analytical capabilities.
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32
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3
Language
Jupyter Notebook
License
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Last pushed
Jan 09, 2026
Commits (30d)
0
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