Merge pull request #158 from linum-uqam/dev-10um-tools

Adding the 10micron option to the script

.gitignore

@@ -148,4 +148,10 @@ dmypy.json
 
 # IDE config files
 .vscode/
-.idea/
+.idea/
+
+# Data
+data/
+*.nii
+*.nii.gz
+*.mat

docs/installation.rst

@@ -11,6 +11,17 @@ We recommend using Anaconda and to install m2m in a separate environment. Execut
     conda activate m2m
     pip install -e .
 
+Update
+======
+
+To update the toolkit, execute the following command.
+
+.. code-block:: bash
+
+    conda activate m2m
+    git pull
+    pip install -e .  # This command is necessary only if the requirements have changed
+
 Notes
 =====
 

m2m/control.py

@@ -9,8 +9,8 @@ def add_overwrite_arg(parser):
 
 def add_resolution_arg(parser):
     parser.add_argument('res', type=int,
-                        choices=[25, 50, 100],
-                        help='Resolution of the Allen files \n'
+                        choices=[10, 25, 50, 100],
+                        help='Resolution (in micron) of the Allen files \n'
                              'Please use the same resolution as '
                              'the transformation matrix.')
 

m2m/version.py

@@ -5,7 +5,7 @@
 # Format expected by setup.py and doc/source/conf.py: string of form "X.Y.Z"
 _version_major = 0
 _version_minor = 1
-_version_micro = 2
+_version_micro = 3
 _version_extra = ''
 
 # Construct full version string from these.

scripts/m2m_compute_transform_matrix.py

@@ -3,7 +3,7 @@
 
 """
     Compute an Affine transformation matrix for a specific resolution 
-    in the Allen (25, 50, 100) using ANTsPyX.
+    in the Allen using ANTsPyX.
 
     Thoses matrices are needed for the other scripts in order 
     to align Allen data on User Data Space.
@@ -48,7 +48,7 @@ def main():
     parser = _build_arg_parser()
     args = parser.parse_args()
 
-    # Verying args validity
+    # Checking args validity
     check_input_file(parser, args.reference)
     if not (args.reference).endswith(".nii") and \
             not (args.reference).endswith(".nii.gz"):
@@ -64,10 +64,10 @@ def main():
     # Loading User template
     user_vol = load_user_template(str(args.reference))
 
-    # Pretransform volumes orientations
+    # Pre-transform volumes orientations
     allen_reorient = pretransform_vol_PIR_UserDataSpace(allen_vol, user_vol)
 
-    # Registrating with ANTsPyX
+    # Registration with ANTsPyX
     affine_mat = compute_transform_matrix(allen_reorient, user_vol, fixed_res=args.user_res, moving_res=args.res)
 
     # Saving the matrix

scripts/m2m_download_annotation.py

@@ -9,6 +9,12 @@
 from allensdk.core.reference_space_cache import ReferenceSpaceCache
 from pathlib import Path
 import SimpleITK as sitk
+import nrrd
+import numpy as np
+import nibabel as nib
+from m2m.transform import (registrate_allen2UserDataSpace)
+from m2m.util import (load_user_template,
+                      save_nifti, )
 
 ALLEN_RESOLUTIONS = [10, 25, 50, 100]
 
@@ -23,6 +29,13 @@ def _build_arg_parser():
     p.add_argument("-r", "--resolution", default=100, type=int, choices=ALLEN_RESOLUTIONS,
                    help="Template resolution in micron. Default=%(default)s")
 
+    # Add optional arguments to align the template to the user space
+    p.add_argument_group("Align the template to the user space")
+    p.add_argument("-m", "--file_mat", default=None, type=str,
+                   help="Path to the transform matrix (.mat)")
+    p.add_argument("-R", "--reference", default=None, type=str,
+                     help="Path to the reference volume (.nii.gz)")
+
     return p
 
 
@@ -64,26 +77,48 @@ def main():
     # Download the brain annotations and structure information - WIP
     # ID 1 is the adult mouse structure graph
     rsp = rspc.get_reference_space(structure_file_name=json_file, annotation_file_name=nrrd_file)
-    rsp.write_itksnap_labels(str(nrrd_file), str(output_labels))
+    rsp.write_itksnap_labels(str(nrrd_file), str(output_labels))  # TODO: this step takes a long time, can we speed it up?
 
     # Loading the nrrd file
-    vol = sitk.ReadImage(str(nrrd_file))
+    vol, metadata = nrrd.read(str(nrrd_file))
 
-    # Preparing the affine to align the template in the RAS+
-    r_mm = args.resolution / 1e3  # Convert the resolution from micron to mm
-    vol.SetSpacing([r_mm] * 3)  # Set the spacing in mm
+    # Converting to PIR to RAS+
+    vol = np.moveaxis(vol, [0, 1, 2], [1, 2, 0])
+    vol = np.flip(vol, axis=1)  # To move from A->P to P->A
+    vol = np.flip(vol, axis=2)  # To move from S->I to I->S
 
-    # Apply the transform
-    vol = sitk.PermuteAxes(vol, (2, 0, 1))
-    vol = sitk.Flip(vol, (False, False, True))
-    vol.SetDirection([1, 0, 0, 0, 1, 0, 0, 0, 1])
+    # Preparing the affine
+    r_mm = args.resolution / 1e3  # Convert the resolution from micron to mm
+    affine = np.eye(4) * r_mm
+    affine[3, 3] = 1
 
     # Save the volume
-    sitk.WriteImage(vol, str(output))
+    img = nib.Nifti1Image(vol, affine)
+    nib.save(img, str(output))
 
     # Remove the temporary files
     nrrd_file.unlink()  # Removes the nrrd file
     json_file.unlink()
 
+    # If the affine matrix was provided, apply it
+    if args.reference is not None and args.file_mat is not None:
+        user_vol = load_user_template(args.reference)
+
+        # Load the allen template
+        allen_vol = load_user_template(str(output))
+        allen_vol = allen_vol.get_fdata()
+
+        # Applying ANTsPyX registration
+        warped_vol = registrate_allen2UserDataSpace(
+            args.file_mat,
+            allen_vol,
+            user_vol,
+            allen_res=args.resolution,
+            smooth=False
+        )
+
+        # Saving the warped volume
+        save_nifti(warped_vol, user_vol.affine, args.output)
+
 if __name__ == "__main__":
     main()

scripts/m2m_download_template.py

@@ -8,7 +8,12 @@
 import argparse
 from allensdk.api.queries.reference_space_api import ReferenceSpaceApi
 from pathlib import Path
-import SimpleITK as sitk
+import numpy as np
+import nibabel as nib
+
+from m2m.transform import (registrate_allen2UserDataSpace)
+from m2m.util import (load_user_template,
+                      save_nifti, )
 
 ALLEN_RESOLUTIONS = [10, 25, 50, 100]
 
@@ -21,6 +26,13 @@ def _build_arg_parser():
     p.add_argument("-r", "--resolution", default=100, type=int, choices=ALLEN_RESOLUTIONS,
                    help="Template resolution in micron. Default=%(default)s")
 
+    # Add optional arguments to align the template to the user space
+    p.add_argument_group("Align the template to the user space")
+    p.add_argument("-m", "--file_mat", default=None, type=str,
+                   help="Path to the transform matrix (.mat)")
+    p.add_argument("-R", "--reference", default=None, type=str,
+                     help="Path to the reference volume (.nii.gz)")
+
     return p
 
 
@@ -44,24 +56,46 @@ def main():
 
     # Downloading the template
     rpa = ReferenceSpaceApi(base_uri=str(output.parent))
-    rpa.download_template_volume(resolution=args.resolution, file_name=nrrd_file)
+    vol, metadata = rpa.download_template_volume(resolution=args.resolution, file_name=nrrd_file)
 
-    # Loading the nrrd file
-    vol = sitk.ReadImage(str(nrrd_file))
+    # Converting to PIR to RAS+
+    vol = np.moveaxis(vol, [0, 1, 2], [1, 2, 0])
+    vol = np.flip(vol, axis=1)  # To move from A->P to P->A
+    vol = np.flip(vol, axis=2)  # To move from S->I to I->S
 
-    # Preparing the affine to align the template in the RAS+
+    # Preparing the affine
     r_mm = args.resolution / 1e3  # Convert the resolution from micron to mm
-    vol.SetSpacing([r_mm] * 3)  # Set the spacing in mm
-
-    # Apply the transform
-    vol = sitk.PermuteAxes(vol, (2, 0, 1))
-    vol = sitk.Flip(vol, (False, False, True))
-    vol.SetDirection([1, 0, 0, 0, 1, 0, 0, 0, 1])
+    affine = np.eye(4) * r_mm
+    affine[3, 3] = 1
 
     # Save the volume
-    sitk.WriteImage(vol, str(output))
+    img = nib.Nifti1Image(vol, affine)
+    nib.save(img, str(output))
     nrrd_file.unlink()  # Removes the nrrd file
 
+    # If the affine matrix was provided, apply it
+    if args.reference is not None and args.file_mat is not None:
+        user_vol = load_user_template(args.reference)
+
+        # Load the allen template
+        allen_vol = load_user_template(str(output))
+        allen_vol = allen_vol.get_fdata()
+
+        # Applying ANTsPyX registration
+        warped_vol = registrate_allen2UserDataSpace(
+            args.file_mat,
+            allen_vol,
+            user_vol,
+            allen_res=args.resolution,
+            smooth=True
+        )
+
+        # Deleting negatives values introduced by b-spline interpolation
+        warped_vol[warped_vol < 0] = 0
+
+        # Saving the warped volume
+        save_nifti(warped_vol, user_vol.affine, args.output)
+
 
 if __name__ == "__main__":
     main()

scripts/m2m_import_proj_density.py

@@ -94,7 +94,7 @@ def _build_arg_parser():
                         'is nearestNeighbor by default.\n'
                         'Using --smooth will change the method to bSpline.')
     p.add_argument('--threshold', type=float, default=.5,
-                   help='Threshold for the binarised map.')
+                   help='Threshold for the binarized map.')
     p.add_argument('--not_all', action="store_true",
                    help='If set, only saves the files specified')
     add_resolution_arg(p)
@@ -112,7 +112,7 @@ def _build_arg_parser():
                    help='Save a binarized projection density map (.nii.gz)'
                         'with a certain --threshold.')
     g.add_argument('--infos', action="store_true",
-                   help='Save informations about the experiment (.json):\n'
+                   help='Save information about the experiment (.json):\n'
                         '- Injection coordinates (MI-Brain, Allen)\n'
                         '- Hemisphere (L or R)\n'
                         '- Injection ROI\n')