bug fixes

TPTBox/core/bids_constants.py

@@ -265,6 +265,8 @@
 
 file_types = [
     "nii.gz",
+    "nii",
+    "nrrd",
     "json",
     "mrk.json",
     "png",
@@ -334,7 +336,7 @@
     # Single class segmentation
     "Label": "label",
     # Others (never used)
-    "Split": "split",
+    "Split": "split",  # Never use, legacy. Is applied inconsistently by other datasets.
     "Density": "den",
     "version": "version",
     "Description": "desc",

TPTBox/core/internal/__init__.py

@@ -1,3 +1,6 @@
 from __future__ import annotations
 
-from .ants_load import ants_to_nifti, nifti_to_ants
+try:
+    from .ants_load import ants_to_nifti, nifti_to_ants
+except ModuleNotFoundError:
+    pass

TPTBox/core/internal/ants_load.py

@@ -9,7 +9,7 @@
     from nibabel.nifti1 import Nifti1Image
 
 
-def nifti_to_ants(nib_image: Nifti1Image):
+def nifti_to_ants(nib_image: Nifti1Image, **args):
     """
     Convert a Nifti image to an ANTsPy image.
 
@@ -23,6 +23,10 @@ def nifti_to_ants(nib_image: Nifti1Image):
     ants_image : ants.ANTsImage
         The converted ANTs image.
     """
+    try:
+        return ants.utils.from_nibabel_nifti(nib_image, **args)
+    except Exception:
+        pass
     ndim = nib_image.ndim
 
     if ndim < 3:
@@ -107,6 +111,10 @@ def ants_to_nifti(img, header=None) -> Nifti1Image:
     img : Nifti1Image
         The converted Nifti image.
     """
+    try:
+        return ants.utils.to_nibabel_nifti(img, header=header)
+    except Exception:
+        pass
     from nibabel.nifti1 import Nifti1Image
 
     affine = get_ras_affine_from_ants(img)

TPTBox/core/nii_wrapper.py

@@ -954,7 +954,10 @@ def n4_bias_field_correction(
         assert self.seg is False, "n4 bias field correction on a segmentation does not make any sense"
         # install antspyx not ants!
         import ants
-        import ants.utils.bias_correction as bc  # install antspyx not ants!
+        try:
+            import ants.ops.bias_correction as bc  # install antspyx not ants!
+        except ModuleNotFoundError:
+            import ants.utils.bias_correction as bc  # install antspyx not ants!
         from ants.utils.convert_nibabel import from_nibabel
         from scipy.ndimage import binary_dilation, generate_binary_structure
         dtype = self.dtype

TPTBox/core/np_utils.py

@@ -1185,7 +1185,16 @@ def np_calc_boundary_mask(
     infect_list = []
 
     def infect(x, y, z):
-        if any([x < 0, y < 0, z < 0, x == boundary.shape[0], y == boundary.shape[1], z == boundary.shape[2]]):
+        if any(
+            [
+                x < 0,
+                y < 0,
+                z < 0,
+                x == boundary.shape[0],
+                y == boundary.shape[1],
+                z == boundary.shape[2],
+            ]
+        ):
             return
         if boundary[x, y, z] == 0:
             boundary[x, y, z] = 1
@@ -1328,7 +1337,6 @@ def np_fill_holes_global_with_majority_voting(arr: UINTARRAY, connectivity: int
             cc_msk,
             label_mask=arr_c,
             dilate_pixel=1,
-            label_ref=1,
             inplace=False,
         )
         arr_c[seg_nii_new != 0] = seg_nii_new[seg_nii_new != 0]
@@ -1355,26 +1363,29 @@ def np_map_labels_based_on_majority_label_mask_overlap(
     Returns:
         arr: input array with all labels in labels relabeled
     """
-    arr_c = arr if inplace else arr.copy()
+    arr_cc = arr if inplace else arr.copy()
 
     labels = _to_labels(arr, label_ref)
 
-    label_list: list[int] = [l for l in np_unique(arr) if l in labels]
-    for l in label_list:
-        arr_l = np_extract_label(arr, l, inplace=False)
+    label_list: list[int] = [label for label in np_unique(arr) if label in labels]
+
+    for label in label_list:
+        arr_l = np_extract_label(arr, label, inplace=False)
         arr_ld = np_dilate_msk(arr_l.copy(), n_pixel=dilate_pixel, label_ref=1, connectivity=3) if dilate_pixel > 0 else arr_l
+        # crop speed up by factor 6
+        crop = np_bbox_binary(arr_ld, px_dist=0, raise_error=False)
 
-        mult = label_mask * arr_ld
+        mult = label_mask[crop] * arr_ld[crop]
         label_ref, count = np.unique(mult, return_counts=True)
         if 0 in label_ref:
             label_ref = label_ref[1:]
             count = count[1:]
         try:
-            newlabel = label_ref[np.argmax(count)]
-        except ValueError:
-            newlabel = no_match_label
-        arr_c[arr_l != 0] = newlabel
-    return arr_c
+            new_label = label_ref[np.argmax(count)]
+        except ValueError:  # should never happen if called from np_fill_holes_global_with_majority_voting
+            new_label = no_match_label
+        arr_cc[arr_l != 0] = new_label
+    return arr_cc
 
 
 def _pad_to_parameters(

TPTBox/tests/test_utils.py

@@ -14,7 +14,6 @@
 import numpy as np  # noqa: E402
 
 import TPTBox.core.bids_files as bids  # noqa: E402
-from TPTBox import Centroids  # noqa: E402
 from TPTBox.core.nii_wrapper import NII  # noqa: E402
 from TPTBox.core.poi import POI  # noqa: E402
 from TPTBox.core.vert_constants import AX_CODES  # noqa: E402

pyproject.toml

@@ -31,6 +31,7 @@ scikit-learn = "*"
 antspyx = "0.4.2"
 pynrrd = "*"
 #hf-deepali = "*"
+requests = "*"
 
 [tool.poetry.group.dev.dependencies]
 pytest = ">=8.1.1"