How imbalanced is your data and how many samples to you have?
I think you might apply some data augmentation (e.g. different level/window settings for the images) to artificially create some more samples. Also affine transformations might be a good strategy. Especially for MRI images I would think you might be brave in using augmentations techniques.
However, let’s dig a bit into the Dataset implementation. How is your data currently stored?
Do you have a folder for each patient with DICOM images in it? If so, do you have different sessions of just different slices?
How many patients, scans, slices do you have?
Based on these information, I’m certain we will come up with a good approach.