B9Kang/MD-S2S-Multidimensional-Self2Self
[MRM 2024] Self-supervised learning for denoising of multidimensional MRI data
This tool helps improve the clarity of complex MRI scans by removing unwanted "noise" from the images. It takes raw, multidimensional MRI data as input and produces cleaner, enhanced MRI images, making it easier to interpret results. It's designed for radiologists, neuroscientists, or medical researchers working with detailed MRI studies who need to improve image quality for diagnosis or analysis.
Use this if you need to quickly and effectively remove noise from your multidimensional MRI datasets without requiring a perfectly clean reference image.
Not ideal if you are working with non-MRI imaging data or require a denoising method that relies on traditional supervised learning with ground truth images.
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Last pushed
Jan 26, 2026
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