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The poor performances of the multi-labels BraTs dataset #138
Description
Activity
I would like to know your batch and the number of training steps
batch_size: 32 and training steps : 30000
Thank you for your answer. My batch is set to 8 and I use A5000GPU. I would like to know the size of the GPU memory you use
I using the four A100 GPUs. And I get the normal mask without brain tissue boundary, but the Dice is lower, about 0.4. So do you have this issue?
I trained 40,000 steps on a gpu and the results are not good and we may need to adjust and improve ourselves
I'm also confused that the loss has leveled off but the results are far from satisfactory
Yes, and I want to know the clamp range in the final "process_xstart" function. I am use (0,3).
This part is not clear to me yet, I am just trying to reproduce and learn the code
Hi！I have trouble with multi-label segmentation. Could you tell me if I want to have a triple classes segmentation (background+label 1+label2), where and which parameters I need to change
The raw images:
The Ground Truth:
The output sample of 5 ensembles:
So why these outputs contain the brain boundary? And how to set 0,1, 2, 4?