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fix a bug: when only need surface distance, it would raise error that…
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… dice did not exist in dictionary.
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@Jingnan-Jia
Jingnan-Jia committed Nov 2, 2021
1 parent c89e22e commit f056208
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Showing 2 changed files with 69 additions and 50 deletions.
117 changes: 68 additions & 49 deletions seg_metrics/seg_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,8 +83,8 @@ def computeQualityMeasures(lP: np.ndarray,
precision = tp / (pred_sum + smooth)
recall = tp / (gdth_sum + smooth)

false_positive_rate = fp / (fp + tn + smooth)
false_negtive_rate = fn / (fn + tp + smooth)
fpr = fp / (fp + tn + smooth)
fnr = fn / (fn + tp + smooth)

jaccard = intersection_sum / (union_sum + smooth)
dice = 2 * intersection_sum / (gdth_sum + pred_sum + smooth)
Expand All @@ -96,9 +96,9 @@ def computeQualityMeasures(lP: np.ndarray,
quality["jaccard"] = jaccard
quality["precision"] = precision
quality["recall"] = recall
quality["false_negtive_rate"] = false_negtive_rate
quality["false_positive_rate"] = false_positive_rate
quality["volume_similarity"] = dicecomputer.GetVolumeSimilarity()
quality["fnr"] = fnr
quality["fpr"] = fpr
quality["vs"] = dicecomputer.GetVolumeSimilarity()
# print('set(distance_metrics).intersection(metrics)', set(distance_metrics).intersection(metrics_names))
# print('set(distance_metrics)', set(distance_metrics))
# print('metrics', metrics_names)
Expand Down Expand Up @@ -150,11 +150,11 @@ def computeQualityMeasures(lP: np.ndarray,
ref2seg_distances = ref2seg_distances + list(np.zeros(num_ref_surface_pixels - len(ref2seg_distances))) #

all_surface_distances = seg2ref_distances + ref2seg_distances
quality["mean_surface_distance"] = np.mean(all_surface_distances)
quality["median_surface_distance"] = np.median(all_surface_distances)
quality["std_surface_distance"] = np.std(all_surface_distances)
quality["95_surface_distance"] = np.percentile(all_surface_distances, 95)
quality["Hausdorff"] = np.max(all_surface_distances)
quality["msd"] = np.mean(all_surface_distances)
quality["mdsd"] = np.median(all_surface_distances)
quality["stdsd"] = np.std(all_surface_distances)
quality["hd95"] = np.percentile(all_surface_distances, 95)
quality["hd"] = np.max(all_surface_distances)
return quality


Expand All @@ -174,18 +174,34 @@ def get_metrics_dict_all_labels(labels: Sequence,
:param fullyConnected: if apply fully connected border during the calculation of surface distance.
:return: metrics_dict_all_labels a dict which contain all metrics
"""
Hausdorff_list = []
Dice_list = []
Jaccard_list = []
Volume_list = []
mean_surface_dis_list = []
median_surface_dis_list = []
std_surface_dis_list = []
nine5_surface_dis_list = []
hd_list = []
dice_list = []
jaccard_list = []
vs_list = []
msd_list = []
mdsd_list = []
stdsd_list = []
hd95_list = []
precision_list = []
recall_list = []
false_positive_rate_list = []
false_negtive_rate_list = []
fpr_list = []
fnr_list = []

label_list = [lb for lb in labels]

metrics_dict_all_labels = {'label': label_list,
'dice': dice_list,
'jaccard': jaccard_list,
'precision': precision_list,
'recall': recall_list,
'fpr': fpr_list,
'fnr': fnr_list,
'vs': vs_list,
'hd': hd_list,
'msd': msd_list,
'mdsd': mdsd_list,
'stdsd': stdsd_list,
'hd95': hd95_list}

for i, label in enumerate(labels):
print('\nstart to get metrics for label: ', label)
Expand All @@ -197,35 +213,38 @@ def get_metrics_dict_all_labels(labels: Sequence,
metrics_names=metrics_names,
fullyConnected=fullyConnected)

Dice_list.append(metrics["dice"])
Jaccard_list.append(metrics["jaccard"])
precision_list.append(metrics["precision"])
recall_list.append(metrics["recall"])
false_negtive_rate_list.append(metrics["false_negtive_rate"])
false_positive_rate_list.append(metrics["false_positive_rate"])
Volume_list.append(metrics["volume_similarity"])

mean_surface_dis_list.append(metrics["mean_surface_distance"])
median_surface_dis_list.append(metrics["median_surface_distance"])
std_surface_dis_list.append(metrics["std_surface_distance"])
nine5_surface_dis_list.append(metrics["95_surface_distance"])
Hausdorff_list.append(metrics["Hausdorff"])

label_list = [lb for lb in labels]

metrics_dict_all_labels = {'label': label_list,
'dice': Dice_list,
'jaccard': Jaccard_list,
'precision': precision_list,
'recall': recall_list,
'fpr': false_positive_rate_list,
'fnr': false_negtive_rate_list,
'vs': Volume_list,
'hd': Hausdorff_list,
'msd': mean_surface_dis_list,
'mdsd': median_surface_dis_list,
'stdsd': std_surface_dis_list,
'hd95': nine5_surface_dis_list}
for k, v in metrics_dict_all_labels.items():
if k in metrics_names:
v.append(metrics[k])
# if "jaccard" in metrics.keys():
# jaccard_list.append(metrics["jaccard"])
# precision_list.append(metrics["precision"])
# recall_list.append(metrics["recall"])
# fnr_list.append(metrics["fnr"])
# fpr_list.append(metrics["fpr"])
# vs_list.append(metrics["vs"])
#
# msd_list.append(metrics["msd"])
# mdsd_list.append(metrics["mdsd"])
# stdsd_list.append(metrics["stdsd"])
# hd95_list.append(metrics["hd95"])
# hd_list.append(metrics["hd"])
#
# label_list = [lb for lb in labels]
#
# metrics_dict_all_labels = {'label': label_list,
# 'dice': dice_list,
# 'jaccard': jaccard_list,
# 'precision': precision_list,
# 'recall': recall_list,
# 'fpr': fpr_list,
# 'fnr': fnr_list,
# 'vs': vs_list,
# 'hd': hd_list,
# 'msd': msd_list,
# 'mdsd': mdsd_list,
# 'stdsd': stdsd_list,
# 'hd95': hd95_list}

metrics_dict = {k: v for k, v in metrics_dict_all_labels.items() if v} # remove empty values

Expand Down
2 changes: 1 addition & 1 deletion setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@

setuptools.setup(
name="seg_metrics", # Replace with your own username
version="1.0.16",
version="1.0.17",
author="Jingnan",
author_email="[email protected]",
description="A package to compute different segmentation metrics for Medical images.",
Expand Down

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