d

RobinNet/dice_gt_seg.py

@@ -80,7 +80,7 @@ def main():
                     seg = onehotencode(seg, autoencoder=True)
 
                     slice_dsc = dice_loss(noisygt, seg)
-                    patient_dsc.append(slice_dsc)
+                    patient_dsc.append(slice_dsc.numpy())
 
                     try:
                         y_true_np = np.squeeze(seg[0, :, :, 0].numpy() > 0.5)
@@ -100,11 +100,9 @@ def main():
                             y_true3d = np.append(np.reshape(y_true_np, newshape=(1, 512, 512)), y_true3d, axis=0)
                     except:
                         pass
-                print("Dice Score for patient", patientnumber, ":", np.mean(patient_dsc))
-                dice_Score16.append(patient_dsc)
 
                 try:
-                    hausdorff_distance_filter = sitk.HausdorffDistanceImgiageFilter()
+                    hausdorff_distance_filter = sitk.HausdorffDistanceImageFilter()
                     hausdorff_distance_filter.Execute(sitk.GetImageFromArray(y_true3d),
                                                       sitk.GetImageFromArray(y_pred3d))
                     hdd3d = hausdorff_distance_filter.GetHausdorffDistance()
@@ -113,7 +111,10 @@ def main():
                 except:
                     pass
 
+                dice_Score16.append(np.mean(patient_dsc))
+                print("Dice Score for patient", patientnumber, np.mean(patient_dsc))
 
+            print("All Dice-Scores for", gt_type, ":", dice_Score16)
             print("All 3d-HDDs for", gt_type, ": ", all3dhdds)
             print("Dice-Score mean: ", np.mean(dice_Score16))
             print("Dice-Score std: ", np.std(dice_Score16))