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Preferred order of augmentations/best practices in documentation #820
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Hi that's a tricky question and I would love to have the answer ... I guess it all depends at the end on the task and the training data ... but even knowing it would not help much to make the choice. So at the end, I personally follow the MRI physics to make the decision. (with the objective to have more physical realist augmentations) for instance, MR noise is additive Gaussian noise added at the end in the Fourier domain, So I keep always the Adding So I would choose something like Ghosting and Spike are more independent (although not sure) but I would put then between bias and motion. Not sure for blur, it is meant to simulated different voxel resolution, I will put it after RandomNoise. And Znormalisation or Salling the intensity to [0 1] should definitively be at the end because this is a transform you will also add on real data before the inference (so same thing for training ... at the end !) I would also recommend to add some RandomGamma to improve the generalization to other scanner / modality ... ->be robust to contrast changes Flip has no physic meaning (just may be issue with bad image header ...) I do not use it (but as far as I understand the order should not matter) A second question is which probability do you choose ? difficult one too ... |
Thank you very much for the very detailed answer! It helped a lot! |
Thank you very much for your great project, it literally saved me countless hours of work!
I wonder whether it would be possible in the documentation to hint how augmentations should generally be ordered ("best practices").
I have the following pipeline and I am quite unsure whether the ordering makes sense, also some augmentations cannot work with
np.uint8
while others can.The text was updated successfully, but these errors were encountered: