feat(syn): Update totalFieldVarianceInVoxel space based on voxel resolution

sdcflows/data/sd_syn.json

@@ -14,7 +14,7 @@
     "shrink_factors": [ [ 1, 1 ], [ 1 ] ],
     "sigma_units": [ "vox", "vox" ],
     "smoothing_sigmas": [ [ 2, 0 ], [ 0 ] ],
-    "transform_parameters": [ [ 0.8, 6.0, 3.0 ], [ 0.8, 2.0, 1.0 ] ],
+    "transform_parameters": [ [ 0.8, 6.0, 10.0 ], [ 0.8, 2.0, 0.5 ] ],
     "transforms": [ "SyN", "SyN" ],
     "use_histogram_matching": [ true, true ],
     "winsorize_lower_quantile": 0.001,

sdcflows/data/sd_syn_sloppy.json

@@ -14,7 +14,7 @@
     "shrink_factors": [ [ 1, 1 ], [ 1 ] ],
     "sigma_units": [ "vox", "vox" ],
     "smoothing_sigmas": [ [ 2, 0 ], [ 0 ] ],
-    "transform_parameters": [ [ 0.8, 6.0, 3.0 ], [ 0.8, 2.0, 1.0 ] ],
+    "transform_parameters": [ [ 0.8, 6.0, 10.0 ], [ 0.8, 2.0, 0.5 ] ],
     "transforms": [ "SyN", "SyN" ],
     "use_histogram_matching": [ true, true ],
     "verbose": true,

sdcflows/workflows/fit/syn.py

@@ -23,6 +23,7 @@
 """
 Estimating the susceptibility distortions without fieldmaps.
 """
+import json
 
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
@@ -214,9 +215,14 @@
     find_zooms = pe.Node(niu.Function(function=_adjust_zooms), name="find_zooms")
     zooms_epi = pe.Node(RegridToZooms(), name="zooms_epi")
 
+    syn_config = data.load(f"sd_syn{'_sloppy' * sloppy}.json")
+
+    vox_params = pe.Node(niu.Function(function=_mm2vox), name="vox_params")
+    vox_params.inputs.registration_config = json.loads(syn_config.read_text())
+
     # SyN Registration Core
     syn = pe.Node(
-        Registration(from_file=data.load(f"sd_syn{'_sloppy' * sloppy}.json")),
+        Registration(from_file=syn_config),
         name="syn",
         n_procs=omp_nthreads,
     )
@@ -277,6 +283,7 @@
                                   ("sd_prior", "in2")]),
         (inputnode, anat_dilmsk, [("anat_mask", "in_file")]),
         (inputnode, warp_dir, [("anat_ref", "fixed_image")]),
+        (inputnode, vox_params, [("anat_ref", "fixed_image")]),
         (inputnode, anat_merge, [("anat_ref", "in1")]),
         (inputnode, lap_anat, [("anat_ref", "op1")]),
         (inputnode, find_zooms, [("anat_ref", "in_anat"),
@@ -295,11 +302,15 @@
         (anat_dilmsk, amask2epi, [("out_file", "input_image")]),
         (amask2epi, epi_umask, [("output_image", "in2")]),
         (readout_time, warp_dir, [("pe_direction", "pe_dir")]),
+        (readout_time, vox_params, [("pe_direction", "pe_dir")]),
+        (clip_epi, warp_dir, [("out_file", "moving_image")]),
+        (clip_epi, vox_params, [("out_file", "moving_image")]),
         (warp_dir, syn, [("out", "restrict_deformation")]),
         (anat_merge, syn, [("out", "fixed_image")]),
         (fixed_masks, syn, [("out", "fixed_image_masks")]),
         (epi_merge, syn, [("out", "moving_image")]),
         (moving_masks, syn, [("out", "moving_image_masks")]),
+        (vox_params, syn, [("out", "transform_parameters")]),
         (syn, extract_field, [(("forward_transforms", _pop), "transform")]),
         (clip_epi, extract_field, [("out_file", "epi")]),
         (readout_time, extract_field, [("readout_time", "ro_time"),
@@ -583,25 +594,52 @@
     return workflow
 
 
-def _warp_dir(fixed_image, pe_dir, nlevels=3):
+def _warp_dir(moving_image, fixed_image, pe_dir, nlevels=3):
     """Extract the ``restrict_deformation`` argument from metadata."""
     import numpy as np
     import nibabel as nb
 
-    img = nb.load(fixed_image)
+    moving = nb.load(moving_image)
+    fixed = nb.load(fixed_image)
 
-    if np.any(nb.affines.obliquity(img.affine) > 0.05):
+    if np.any(nb.affines.obliquity(fixed.affine) > 0.05):
         from nipype import logging
 
         logging.getLogger("nipype.interface").warn(
             "Running fieldmap-less registration on an oblique dataset"
         )
 
-    vs = nb.affines.voxel_sizes(img.affine)
-    order = np.around(np.abs(img.affine[:3, :3] / vs))
-    retval = order @ [1 if pe_dir[0] == ax else 0.1 for ax in "ijk"]
+    moving_axcodes = nb.aff2axcodes(moving.affine, ["RR", "AA", "SS"])
+    moving_pe_axis = moving_axcodes["ijk".index(pe_dir[0])]
+
+    fixed_axcodes = nb.aff2axcodes(fixed.affine, ["RR", "AA", "SS"])
+
+    deformation = [0.1, 0.1, 0.1]
+    deformation[fixed_axcodes.index(moving_pe_axis)] = 1.0
+
+    return nlevels * [deformation]
+
+
+def _mm2vox(moving_image, fixed_image, pe_dir, registration_config):
+    import nibabel as nb
+
+    params = registration_config['transform_parameters']
+
+    moving = nb.load(moving_image)
+    # Use duplicate axcodes to ignore sign
+    moving_axcodes = nb.aff2axcodes(moving.affine, ["RR", "AA", "SS"])
+    moving_pe_axis = moving_axcodes["ijk".index(pe_dir[0])]
+
+    fixed = nb.load(fixed_image)
+    fixed_axcodes = nb.aff2axcodes(fixed.affine, ["RR", "AA", "SS"])
+
+    zooms = nb.affines.voxel_sizes(fixed.affine)
+    pe_res = zooms[fixed_axcodes.index(moving_pe_axis)]
 
-    return nlevels * [retval.tolist()]
+    return [
+        [*level_params[:2], level_params[2] / pe_res]
+        for level_params in params
+    ]
 
 
 def _merge_meta(epi_ref, meta_list):

sdcflows/workflows/fit/tests/test_syn.py

@@ -23,10 +23,20 @@
 """Test fieldmap-less SDC-SyN."""
 
 import json
+
+import numpy as np
+import nibabel as nb
 import pytest
 from nipype.pipeline import engine as pe
 
-from ..syn import init_syn_sdc_wf, init_syn_preprocessing_wf, _adjust_zooms, _set_dtype
+from .... import data
+from ..syn import (
+    init_syn_sdc_wf,
+    init_syn_preprocessing_wf,
+    _adjust_zooms,
+    _set_dtype,
+    _mm2vox,
+)
 
 
 @pytest.mark.veryslow
@@ -254,3 +264,56 @@ def test_ensure_dtype(in_dtype, out_dtype, tmpdir):
         assert out_file == f"{in_dtype}.nii.gz"
     else:
         assert out_file == f"{in_dtype}_{out_dtype}.nii.gz"
+
+
+def axcodes2aff(axcodes):
+    """Return an affine matrix from axis codes."""
+    return nb.orientations.inv_ornt_aff(
+        nb.orientations.ornt_transform(
+            nb.orientations.axcodes2ornt("RAS"),
+            nb.orientations.axcodes2ornt(axcodes),
+        ),
+        (10, 10, 10),
+    )
+
+
+@pytest.mark.parametrize(
+    ("fixed_ornt", "moving_ornt", "ijk", "index"),
+    [
+        ("RAS", "RAS", "i", 0),
+        ("RAS", "RAS", "j", 1),
+        ("RAS", "RAS", "k", 2),
+        ("RAS", "PSL", "i", 1),
+        ("RAS", "PSL", "j", 2),
+        ("RAS", "PSL", "k", 0),
+        ("PSL", "RAS", "i", 2),
+        ("PSL", "RAS", "j", 0),
+        ("PSL", "RAS", "k", 1),
+    ],
+)
+def test_mm2vox(tmp_path, fixed_ornt, moving_ornt, ijk, index):
+    fixed_path = tmp_path / "fixed.nii.gz"
+    moving_path = tmp_path / "moving.nii.gz"
+
+    # Use separate zooms to make identifying the conversion easier
+    fixed_aff = np.diag((2, 3, 4, 1))
+    nb.save(
+        nb.Nifti1Image(np.zeros((10, 10, 10)), axcodes2aff(fixed_ornt) @ fixed_aff),
+        fixed_path,
+    )
+    nb.save(
+        nb.Nifti1Image(np.zeros((10, 10, 10)), axcodes2aff(moving_ornt)),
+        moving_path,
+    )
+
+    config = json.loads(data.load.readable("sd_syn.json").read_text())
+
+    params = config["transform_parameters"]
+    mm_values = np.array([level[2] for level in params])
+
+    vox_params = _mm2vox(str(moving_path), str(fixed_path), ijk, config)
+    vox_values = [level[2] for level in vox_params]
+    assert [
+        mm_level[:2] == vox_level[:2] for mm_level, vox_level in zip(params, vox_params)
+    ]
+    assert np.array_equal(vox_values, mm_values / [2, 3, 4][index])