smart-primate/MRI_Style_Transfer_using_CycleGAN
Build a Generative adversarial model (modified U-Net) which can generate artificial MRI images of different contrast levels from existing MRI scans.
This tool helps radiologists and medical professionals generate different variations of MRI scans from existing images. You provide an MRI scan of one contrast level (e.g., T1-weighted), and it produces an artificial MRI scan of a different contrast level (e.g., T2-weighted). This allows for a more comprehensive understanding of the image, potentially improving diagnostic accuracy and reducing misdiagnosis.
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Use this if you need to view an MRI scan in multiple contrast variations for a more complete diagnostic picture, without the expense or difficulty of acquiring additional scans.
Not ideal if you require entirely new, original MRI scans rather than 'style-transferred' variations from an existing image.
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Jupyter Notebook
License
MIT
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Last pushed
Apr 03, 2022
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