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Since we want to train on both 2D (X-ray) and 3D data (CT and MRI), we need DINOv2 to work on 3D as well. A simple way of extending it is to apply identical spatial/color/noise transformations across slices, then investigate tube vs random masking across the slices.
The text was updated successfully, but these errors were encountered:
Since we want to train on both 2D (X-ray) and 3D data (CT and MRI), we need DINOv2 to work on 3D as well. A simple way of extending it is to apply identical spatial/color/noise transformations across slices, then investigate tube vs random masking across the slices.
The text was updated successfully, but these errors were encountered: