def test_empty_mask_in_gt(self):
# test empty mask in ground truth
mask_gt = np.zeros((128, 128, 128), np.uint8)
mask_pred = np.zeros((128, 128, 128), np.uint8)
# mask_gt[50,60,70] = 1
mask_pred[50, 60, 72] = 1
surface_distances = compute_surface_distances(mask_gt, mask_pred, spacing_mm=(3, 2, 1))
average_surface_distance = compute_average_surface_distance(surface_distances)
hausdorf_100 = compute_robust_hausdorff(surface_distances, 100)
hausdorf_95 = compute_robust_hausdorff(surface_distances, 95)
surface_overlap_1_mm = compute_surface_overlap_at_tolerance(surface_distances, 1)
surface_dice_1mm = compute_surface_dice_at_tolerance(surface_distances, 1)
volumetric_dice = compute_dice_coefficient(mask_gt, mask_pred)
print("average surface distance: {} mm".format(average_surface_distance))
print("hausdorff (100%): {} mm".format(hausdorf_100))
print("hausdorff (95%): {} mm".format(hausdorf_95))
print("surface overlap at 1mm: {}".format(surface_overlap_1_mm))
print("surface dice at 1mm: {}".format(surface_dice_1mm))
print("volumetric dice: {}".format(volumetric_dice))
self.assertAlmostEqual(surface_dice_1mm, 0.0, delta=self.delta)
self.assertAlmostEqual(volumetric_dice, 0.0, delta=self.delta)
def test_single_pixels_2mm_away(self):
mask_gt = np.zeros((128, 128, 128), np.uint8)
mask_pred = np.zeros((128, 128, 128), np.uint8)
mask_gt[50, 60, 70] = 1
mask_pred[50, 60, 72] = 1
surface_distances = compute_surface_distances(mask_gt, mask_pred, spacing_mm=(3, 2, 1))
surface_dice_1mm = compute_surface_dice_at_tolerance(surface_distances, 1)
volumetric_dice = compute_dice_coefficient(mask_gt, mask_pred)
print("surface dice at 1mm: {}".format(surface_dice_1mm))
print("volumetric dice: {}".format(volumetric_dice))
self.assertAlmostEqual(surface_dice_1mm, 0.5, delta=self.delta)
self.assertAlmostEqual(volumetric_dice, 0.0, delta=self.delta)
def test_surface_dice(self):
path = "images\\img{}\\instrument_instances.png".format(3)
# read image
x = imread(path)
# make image binary
x[x < 0.5] = 0
x[x >= 0.5] = 1
mask_gt = np.reshape(x, x.shape + (1,))
surface_distances = compute_surface_distances(mask_gt, mask_gt, (1, 1, 1))
def test_two_cubes(self):
# two cubes. cube 1 is 100x100x100 mm^3 and cube 2 is 102x100x100 mm^3
mask_gt = np.zeros((100, 100, 100), np.uint8)
mask_pred = np.zeros((100, 100, 100), np.uint8)
spacing_mm = (2, 1, 1)
mask_gt[0:50, :, :] = 1
mask_pred[0:51, :, :] = 1
surface_distances = compute_surface_distances(mask_gt, mask_pred, spacing_mm)
expected_average_distance_gt_to_pred = 0.836145008498
expected_volumetric_dice = 2. * 100 * 100 * 100 / (100 * 100 * 100 + 102 * 100 * 100)
surface_dice_1mm = compute_surface_dice_at_tolerance(surface_distances, 1)
volumetric_dice = compute_dice_coefficient(mask_gt, mask_pred)
print("surface dice at 1mm: {}".format(compute_surface_dice_at_tolerance(surface_distances, 1)))
print("volumetric dice: {}".format(compute_dice_coefficient(mask_gt, mask_pred)))
self.assertAlmostEqual(surface_dice_1mm, expected_average_distance_gt_to_pred, delta=self.delta)
self.assertAlmostEqual(volumetric_dice, expected_volumetric_dice, delta=self.delta)