Comments (2)
Hi,
I think this was already discussed in this thread: #8
The rationale, when I implemented it, was that we compute the distance to the boundary. By this logic, the distance of the boundary wrt the boundary should be 0. Since this not the behavior of the SciPy function distance_transform_edt. I did that manually by shifting the distance by 1 on the distance to the positive mask.
To be fair, I do not think it would change (much) the results, since it is only shifting the distance values inside the object. But I did not had time to compare the impact of this implementation detail.
Does it answer your question?
Best,
Hoel
from boundary-loss.
Thanks
from boundary-loss.
Related Issues (20)
- Does einsum really make the code easier to understand HOT 2
- ISLES 2018 HOT 1
- Heterogeneous resolution yields non-zero boundary. HOT 5
- InvalidArgumentError: required broadcastable shapes at loc(unknown) [Op:Mul] HOT 2
- Can this loss be used for multi-label classification? HOT 4
- Create dist_map for image segmentation mask as label. HOT 2
- Is multiplication by negmask in one_hot2dist() irrelevant? HOT 2
- Question about the optional argument resolution in the dist_map_transform function HOT 1
- About the calculation of dist_map HOT 5
- how to use with sigmoid as activation function when meeting binary classification segmentation task HOT 3
- how to adjust the lambda parameter HOT 5
- How to use HausdorffLoss? HOT 1
- How to use HausdorffLoss? HOT 1
- How to one-hot encode a multi-class dataset and how to use Boundary Loss on B x N x W x H logits? HOT 2
- Only using boundary loss leads to non convergence HOT 1
- Failure of matching datasets of WMH HOT 1
- Is it possible to train the Boundary Loss code on a GPU? HOT 1
- Whether this loss function can be applied to the partition of a hollow region, that is, a region with two boundaries HOT 2
- License Request
- zero question
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