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Adding a loss mask?

See original GitHub issue

Are there any plans to add an easy way to include “loss mask” to Dataset class for segmentation task? As what I understood, it only takes img and seg?

For example I have such CT volumes with the following “windowing” that could be masked away

image

And in general the following behavior could be a nice feature

https://github.com/deepmind/deepmind-research/blob/cf0a9ca46058a61e8b66bc8708cd35ac77209bc6/hierarchical_probabilistic_unet/geco_utils.py#L100

Issue Analytics

  • State:closed
  • Created 3 years ago
  • Comments:6 (3 by maintainers)

github_iconTop GitHub Comments

1reaction
wylicommented, Jun 5, 2021

sure @eddyleelin, let me look into this…

0reactions
eddyleelincommented, Jun 5, 2021

Sorry, could I ask what is the current status of this issue? @wyli It seems like currently MaskedDiceLoss is the only type of segmentation loss with an implementation of masking. Would it be beneficial to extend masking to the other segmentation losses, such as Tversky or Focal Losses? Perhaps with a wrapper function like MultiScaleLoss? Thanks 😄

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