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3788 avg surface distance update #3824

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Merged
wyli merged 2 commits into from
Feb 21, 2022
Merged

3788 avg surface distance update #3824

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403b3ad
fixes #3788 according to the suggestions
wyli Feb 20, 2022
b82f370
Merge branch 'dev' into 3788-avg-surface-dist
wyli Feb 21, 2022
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20 changes: 5 additions & 15 deletions monai/metrics/surface_distance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@
import torch

from monai.metrics.utils import do_metric_reduction, get_mask_edges, get_surface_distance, ignore_background
from monai.utils import MetricReduction
from monai.utils import MetricReduction, convert_data_type

from .metric import CumulativeIterationMetric

Expand Down Expand Up @@ -153,20 +153,10 @@ def compute_average_surface_distance(
warnings.warn(f"the ground truth of class {c} is all 0, this may result in nan/inf distance.")
if not np.any(edges_pred):
warnings.warn(f"the prediction of class {c} is all 0, this may result in nan/inf distance.")

surface_distance = get_surface_distance(edges_pred, edges_gt, distance_metric=distance_metric)
if surface_distance.shape == (0,):
avg_surface_distance = np.nan
else:
avg_surface_distance = surface_distance.mean()
if not symmetric:
asd[b, c] = avg_surface_distance
else:
if symmetric:
surface_distance_2 = get_surface_distance(edges_gt, edges_pred, distance_metric=distance_metric)
if surface_distance_2.shape == (0,):
avg_surface_distance_2 = np.nan
else:
avg_surface_distance_2 = surface_distance_2.mean()
asd[b, c] = np.mean((avg_surface_distance, avg_surface_distance_2))
surface_distance = np.concatenate([surface_distance, surface_distance_2])
asd[b, c] = np.nan if surface_distance.shape == (0,) else surface_distance.mean()

return torch.from_numpy(asd)
return convert_data_type(asd, torch.Tensor)[0]
14 changes: 7 additions & 7 deletions tests/test_surface_distance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,30 +61,30 @@ def create_spherical_seg_3d(
create_spherical_seg_3d(radius=33, centre=(19, 33, 22)),
create_spherical_seg_3d(radius=33, centre=(20, 33, 22)),
],
[0.35021200688332677, 0.3483278807706289],
[0.350217, 0.3483278807706289],
],
[
[
create_spherical_seg_3d(radius=20, centre=(20, 33, 22)),
create_spherical_seg_3d(radius=40, centre=(20, 33, 22)),
],
[13.975673696300824, 12.040033513150455],
[15.117741, 12.040033513150455],
],
[
[
create_spherical_seg_3d(radius=20, centre=(20, 33, 22)),
create_spherical_seg_3d(radius=40, centre=(20, 33, 22)),
"chessboard",
],
[10.792254295459173, 9.605067064083457],
[11.492719, 9.605067064083457],
],
[
[
create_spherical_seg_3d(radius=20, centre=(20, 33, 22)),
create_spherical_seg_3d(radius=40, centre=(20, 33, 22)),
"taxicab",
],
[17.32691760951026, 12.432687531048186],
[20.214613, 12.432687531048186],
],
[[np.zeros([99, 99, 99]), create_spherical_seg_3d(radius=40, centre=(20, 33, 22))], [np.inf, np.inf]],
[[create_spherical_seg_3d(), np.zeros([99, 99, 99]), "taxicab"], [np.inf, np.inf]],
Expand Down Expand Up @@ -121,7 +121,7 @@ def test_value(self, input_data, expected_value):
sur_metric(batch_seg_1, batch_seg_2)
result = sur_metric.aggregate()
expected_value_curr = expected_value[ct]
np.testing.assert_allclose(expected_value_curr, result, rtol=1e-7)
np.testing.assert_allclose(expected_value_curr, result, rtol=1e-5)
ct += 1

@parameterized.expand(TEST_CASES_NANS)
Expand All @@ -135,8 +135,8 @@ def test_nans(self, input_data):
batch_seg_2 = [seg_2.unsqueeze(0)]
sur_metric(batch_seg_1, batch_seg_2)
result, not_nans = sur_metric.aggregate()
np.testing.assert_allclose(0, result, rtol=1e-7)
np.testing.assert_allclose(0, not_nans, rtol=1e-7)
np.testing.assert_allclose(0, result, rtol=1e-5)
np.testing.assert_allclose(0, not_nans, rtol=1e-5)


if __name__ == "__main__":
Expand Down