Comments (5)
Actually, the 'Seg_norm' function in /data/trans.py can convert discontinuous labels into continuous ones. So when calculating the Dice metric, continuous labels can be used naturally.
from smilecode.
Thank you for your prompt response. I have now prepared my own dataset in '.pkl' format. Can I use your data reading logic to perform the inter-patient brain MR registration task? Apart from modifying 'seg_table' in the 'Seg_norm' function to match the labels of my own data, do I need to customize the values in the 'VOI_lbls' list?
from smilecode.
As a side note, I have encapsulated my dataset in a manner consistent with the 'TransMorph' approach.
from smilecode.
The seg_table and seg_list should be changed along with the dataset changes.
from smilecode.
Thank you once again for your response amidst your busy schedule. My question has been resolved. Wishing you success in your work and studies!
from smilecode.
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