General Space Conversion

docs/references/localization.rst

@@ -13,6 +13,10 @@ Convert from FSAverage to MNI152
 
 .. autofunction:: fsaverage_to_mni152
 
+Convert from any source space to any target space
+------------------------------------------------
+
+.. autofunction:: src_to_dst
 
 Localization on a Freesurfer Brain
 ----------------------------------

naplib/localization/__init__.py

@@ -1,4 +1,4 @@
 from .freesurfer import Brain, find_closest_vertices
-from .coordinate_conversions import mni152_to_fsaverage, fsaverage_to_mni152
+from .coordinate_conversions import mni152_to_fsaverage, fsaverage_to_mni152, src_to_dst
 
-__all__ = ['Brain', 'find_closest_vertices', 'mni152_to_fsaverage', 'fsaverage_to_mni152']
+__all__ = ['Brain', 'find_closest_vertices', 'mni152_to_fsaverage', 'fsaverage_to_mni152', 'src_to_dst']

naplib/localization/coordinate_conversions.py

@@ -1,4 +1,7 @@
 import numpy as np
+import nibabel.freesurfer.io as fsio
+from scipy.spatial import cKDTree
+import nibabel as nib
 
 def mni152_to_fsaverage(coords):
     """
@@ -38,4 +41,142 @@ def fsaverage_to_mni152(coords):
     new_coords = (xform @ old_coords).T
     return new_coords
 
+def src_to_dst(coords, src_pial, src_sphere, dst_pial, dst_sphere, require_lh_mask=False, threshold=100, distance_report=False, verbose=False):
+    """
+    Convert 3D coordinates from any space to another space.
+    Each subject comes with a bunch of MRI files; In this function these files are used:
+    1. lh.pial file of the source space      ==> SRC_PATH/surf/lh.pial
+    2. lh.sphere.reg file of the source      ==> SRC_PATH/surf/lh.sphere.reg
+    3. lh.pial file of the destination       ==> DST_PATH/surf/lh.pial
+    4. lh.sphere.reg file of the destination ==> DST_PATH/surf/lh.sphere.reg
+
+    fsLR is also supported: files ending with .gii
+
+    Provide LH files, the function assumes the RH ones are in the same directory.
+
+    NOTE: In case of converting to an atlas space, the files we need are accessible
+    by installing freesurfer: https://surfer.nmr.mgh.harvard.edu/fswiki/DownloadAndInstall
+    Path of different atlas spaces: PATH_freesurfer/8.0.0/subjects/
+
+    Parameters
+    ----------
+    coords : np.ndarray (elecs, 3)
+        Coordinates in source space. Can be in both hemispheres.
+    src_pial : str/dict{'vert_lh', 'vert_rh'}
+        Path to the source pial surface file (e.g., 'lh.pial'). In case of a mat file for pial surfaces,
+        provide a dictionary with keys 'vert_lh' and 'vert_rh' containing the vertices for each hemisphere.
+    src_sphere : str
+        Path to the source sphere file (e.g., 'lh.sphere.reg')
+    dst_pial : str
+        Path to the destination pial surface file (e.g., 'lh.pial')
+    dst_sphere : str
+        Path to the destination sphere file (e.g., 'lh.sphere.reg')
+    require_lh_mask : bool, optional
+        If True, returns a mask indicating which coordinates are in the left hemisphere. Default is False.
+    threshold : float, optional
+        Maximum distance in mm for an electrode to be considered in cortex (not in depth).
+    distance_report : bool, optional
+        If True, returns the distance of each coordinate to the nearest vertex. Default is False.
+    verbose : bool, optional
+        If True, prints additional information about the conversion process. Default is False.
+
+    Returns
+    -------
+    new_coords : np.ndarray (elecs, 3)
+        Coordinates in target space
+    lh_mask : np.ndarray (elecs,)
+        Mask indicating which coordinates are in the left hemisphere (if `require_lh_mask` is True)
+    distance : np.ndarray (elecs,) or None
+        Distance of each coordinate to the nearest vertex in the source pial surface (if `distance_report` is True)
+    """
+
+    if not src_sphere.endswith('.surf.gii'):
+        src_sphere_lh, _ = fsio.read_geometry(src_sphere)
+        src_sphere_rh, _ = fsio.read_geometry(src_sphere.replace('lh', 'rh'))
+        src_sphere = np.vstack((src_sphere_lh, src_sphere_rh))
+    else:
+        sphere_lh = nib.load(src_sphere)
+        src_sphere_lh = sphere_lh.darrays[0].data
+        sphere_rh = nib.load(src_sphere.replace('.L.', '.R.'))
+        src_sphere_rh = sphere_rh.darrays[0].data
+        src_sphere = np.vstack((src_sphere_lh, src_sphere_rh))
+
+    if not dst_sphere.endswith('.surf.gii'):
+        tgt_sphere_lh, _ = fsio.read_geometry(dst_sphere)
+        tgt_sphere_rh, _ = fsio.read_geometry(dst_sphere.replace('lh', 'rh'))
+    else:
+        sphere_lh = nib.load(dst_sphere)
+        tgt_sphere_lh = sphere_lh.darrays[0].data
+        sphere_rh = nib.load(dst_sphere.replace('.L.', '.R.'))
+        tgt_sphere_rh = sphere_rh.darrays[0].data
+
+    tree_lh = cKDTree(tgt_sphere_lh)
+    tree_rh = cKDTree(tgt_sphere_rh)
+
+    nan_list = np.zeros(coords.shape[0], dtype=bool)
+    if np.isnan(coords).any() or (np.sum(np.abs(coords),axis=1)==0).any():
+        print(f"WARNING: number of NaN values found in coordinates: {np.sum(np.isnan(coords))}.")
+        nan_list = np.isnan(coords)
+        coords = np.nan_to_num(coords)
+
+    if isinstance(src_pial, str):
+        if not src_pial.endswith('.surf.gii'):
+            lh_verts_sub, _ = fsio.read_geometry(src_pial)
+            rh_verts_sub = fsio.read_geometry(src_pial.replace('lh', 'rh'))[0]
+            lh_threshold = lh_verts_sub.shape[0]
+            lh_verts_sub = np.vstack((lh_verts_sub, rh_verts_sub))
+        else:
+            lh_verts_sub = nib.load(src_pial).darrays[0].data
+            rh_verts_sub = nib.load(src_pial.replace('.L.', '.R.')).darrays[0].data
+            lh_threshold = lh_verts_sub.shape[0]
+            lh_verts_sub = np.vstack((lh_verts_sub, rh_verts_sub))
+    else:
+        lh_verts_sub = src_pial['vert_lh']
+        rh_verts_sub = src_pial['vert_rh']
+        lh_threshold = lh_verts_sub.shape[0]
+
+    if not dst_pial.endswith('.surf.gii'):
+        lh_verts_sub_fs, _ = fsio.read_geometry(dst_pial)
+        rh_verts_sub_fs, _ = fsio.read_geometry(dst_pial.replace('lh', 'rh'))
+    else:
+        lh_verts_sub_fs = nib.load(dst_pial).darrays[0].data
+        rh_verts_sub_fs = nib.load(dst_pial.replace('.L.', '.R.')).darrays[0].data
+
+    tree_elecs = cKDTree(lh_verts_sub)
+    distance, mapping_indices_elecs = tree_elecs.query(coords, k=1)
+
+    if np.any(distance > threshold):
+        print(f"WARNING: Number of in depth electrodes (distance > {threshold} mm): {np.sum(distance > threshold)}")
+        new_nans = distance > threshold
+        nan_list[new_nans] = True
+
+    if verbose:
+        print(f"#Electrodes in LH: {np.sum(mapping_indices_elecs < lh_threshold)}, RH: {np.sum(mapping_indices_elecs >= lh_threshold)}")
+
+    mapping_indices_elecs_lh = mapping_indices_elecs[mapping_indices_elecs < lh_threshold]
+    _, mapping_indices_elecs_warped_lh = tree_lh.query(src_sphere[mapping_indices_elecs_lh], k=1)
+
+    mapping_indices_elecs_rh = mapping_indices_elecs[mapping_indices_elecs >= lh_threshold]
+    _, mapping_indices_elecs_warped_rh = tree_rh.query(src_sphere[mapping_indices_elecs_rh], k=1)
+
+    new_coords_lh = lh_verts_sub_fs[mapping_indices_elecs_warped_lh]
+    new_coords_rh = rh_verts_sub_fs[mapping_indices_elecs_warped_rh]
+
+    new_coords = np.zeros((coords.shape[0], 3))
+    new_coords[mapping_indices_elecs < lh_threshold] = new_coords_lh
+    new_coords[mapping_indices_elecs >= lh_threshold] = new_coords_rh
+    lh_mask = mapping_indices_elecs < lh_threshold
+
+    new_coords[nan_list] = np.nan
 
+    if require_lh_mask:
+        if distance_report:
+            return new_coords, lh_mask, distance
+        else:
+            return new_coords, lh_mask
+    else:
+        if distance_report:
+            return new_coords, distance
+        else:
+            return new_coords
+

tests/test_coordinate_conversions.py

@@ -1,5 +1,7 @@
 import numpy as np
-from naplib.localization import mni152_to_fsaverage, fsaverage_to_mni152
+import os
+import mne
+from naplib.localization import mni152_to_fsaverage, fsaverage_to_mni152, src_to_dst
 
 def test_mni152_fsaverage_conversions():
   coords_tmp = np.array([[13.987, 36.5, 10.067], [-10.54, 24.5, 15.555]])
@@ -12,3 +14,18 @@ def test_mni152_fsaverage_conversions():
 
   coords_tmp3 = fsaverage_to_mni152(coords_tmp2)
   assert np.allclose(coords_tmp3, coords_tmp, rtol=1e-3)
+
+def test_src_to_dst():
+  coords = np.random.rand(2, 3) * 5
+
+  os.makedirs('./.fsaverage_tmp2', exist_ok=True)
+  mne.datasets.fetch_fsaverage('./.fsaverage_tmp2/')
+
+  src_pial = './.fsaverage_tmp2/fsaverage/surf/lh.pial'
+  src_sphere = './.fsaverage_tmp2/fsaverage/surf/lh.sphere.reg'
+  dst_pial = './.fsaverage_tmp2/fsaverage/surf/lh.inflated'
+  dst_sphere = './.fsaverage_tmp2/fsaverage/surf/lh.sphere.reg'
+
+  inflated_coords = src_to_dst(coords, src_pial, src_sphere, dst_pial, dst_sphere)
+
+  assert inflated_coords.shape[0] == coords.shape[0]