Emmanuel comments

scilpy/image/labels.py

@@ -96,11 +96,17 @@ def get_labels_from_mask(mask_data, labels=None, background_label=0,
     # Get the number of structures and assign labels to each blob
     label_map, nb_structures = ndi.label(mask_data)
     if min_voxel_count:
+        new_count = 0
         for label in range(1, nb_structures + 1):
             if np.count_nonzero(label_map == label) < min_voxel_count:
                 label_map[label_map == label] = 0
-        mask_data = label_map > 0
-        label_map, nb_structures = ndi.label(mask_data)
+            else:
+                new_count += 1
+                label_map[label_map == label] = new_count
+        logging.debug(
+            f"Ignored blob {nb_structures-new_count} with fewer "
+            "than {min_voxel_count} voxels")
+        nb_structures = new_count
 
     # Assign labels to each blob if provided
     if labels:

scripts/scil_lesions_info.py

@@ -10,10 +10,6 @@
 Then, the second input can either be streamlines, binary bundle mask, or a
 bundle voxel label map.
 
-To be considered a valid lesion, the lesion volume must be at least
---min_lesion_vol mm3. This avoid the detection of thousand of single voxel
-lesions if an automatic lesion segmentation tool is used.
-
 Formerly: scil_analyse_lesions_load.py
 """
 

scripts/tests/test_labels_from_mask.py

@@ -24,7 +24,7 @@ def test_execution(script_runner, monkeypatch):
                            'bundle_4_head_tail_offset.nii.gz')
     ret = script_runner.run('scil_labels_from_mask.py',
                             in_mask, 'labels_from_mask.nii.gz',
-                            '-f')
+                            '--min_volume', '0', '-f')
     assert ret.success