🔀 Merge hotfix/1.8.7-1 into hotfix/1.8.7-bids-validator

.github/Dockerfiles/base-standard.Dockerfile

@@ -25,6 +25,10 @@ USER root
 # Installing FreeSurfer
 RUN apt-get update \
     && apt-get install --no-install-recommends -y bc \
+    && if [ ! -e /lib/x86_64-linux-gnu/libcrypt.so.2 ]; then \
+    # until we upgrade to Python >=3.11
+      ln -s /lib/x86_64-linux-gnu/libcrypt.so.1 /lib/x86_64-linux-gnu/libcrypt.so.2; \
+    fi \
     && yes | mamba install tcsh \
     && yes | mamba clean --all \
     && cp -l `which tcsh` /bin/tcsh \

CHANGELOG.md

@@ -16,9 +16,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [1.8.7.post1.dev3] - unreleased
 
+### Added
+
+- `desired_orientation` key in participant-level pipeline config under `pipeline_setup`.
+- Required positional parameter "wf" in input and output of `ingress_pipeconfig_paths` function, where a node to reorient templates is added to the `wf`.
+- Required positional parameter "orientation" to `resolve_resolution`.
+- Optional positional argument "cfg" to `create_lesion_preproc`.
+- Validation node to match the pixdim4 of CPAC processed bold outputs with the original raw bold sources.
+
 ### Changed
 
 - Disabled variant image builds.
+- Made orientation configurable (was hard-coded as "RPI").
 
 ### Fixed
 

CPAC/anat_preproc/anat_preproc.py

@@ -1056,7 +1056,7 @@ def freesurfer_fsl_brain_connector(wf, cfg, strat_pool, pipe_num, opt):
                                     name=f'reorient_fs_brainmask_{node_id}',
                                     mem_gb=0,
                                     mem_x=(0.0115, 'in_file', 't'))
-    reorient_fs_brainmask.inputs.orientation = 'RPI'
+    reorient_fs_brainmask.inputs.orientation = cfg.pipeline_setup["desired_orientation"]
     reorient_fs_brainmask.inputs.outputtype = 'NIFTI_GZ'
 
     wf.connect(convert_fs_brainmask_to_nifti, 'out_file', 
@@ -1075,7 +1075,7 @@ def freesurfer_fsl_brain_connector(wf, cfg, strat_pool, pipe_num, opt):
                              name=f'reorient_fs_T1_{node_id}',
                              mem_gb=0,
                              mem_x=(0.0115, 'in_file', 't'))
-    reorient_fs_T1.inputs.orientation = 'RPI'
+    reorient_fs_T1.inputs.orientation = cfg.pipeline_setup["desired_orientation"]
     reorient_fs_T1.inputs.outputtype = 'NIFTI_GZ'
 
     wf.connect(convert_fs_T1_to_nifti, 'out_file', 
@@ -1279,18 +1279,20 @@ def anatomical_init(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data('T1w')
     wf.connect(node, out, anat_deoblique, 'in_file')
 
-    anat_reorient = pe.Node(interface=afni.Resample(),
-                            name=f'anat_reorient_{pipe_num}',
-                            mem_gb=0,
-                            mem_x=(0.0115, 'in_file', 't'))
-    anat_reorient.inputs.orientation = 'RPI'
-    anat_reorient.inputs.outputtype = 'NIFTI_GZ'
-
-    wf.connect(anat_deoblique, 'out_file', anat_reorient, 'in_file')
-
-    outputs = {'desc-preproc_T1w': (anat_reorient, 'out_file'),
-               'desc-reorient_T1w': (anat_reorient, 'out_file'),
-               'desc-head_T1w': (anat_reorient, 'out_file')}
+    anat_reorient = pe.Node(
+        interface=afni.Resample(),
+        name=f"anat_reorient_{pipe_num}",
+        mem_gb=0,
+        mem_x=(0.0115, "in_file", "t"),
+    )
+    anat_reorient.inputs.orientation = cfg.pipeline_setup["desired_orientation"]
+    anat_reorient.inputs.outputtype = "NIFTI_GZ"
+    wf.connect(anat_deoblique, "out_file", anat_reorient, "in_file")
+    outputs = {
+        "desc-preproc_T1w": (anat_reorient, "out_file"),
+        "desc-reorient_T1w": (anat_reorient, "out_file"),
+        "desc-head_T1w": (anat_reorient, "out_file"),
+    }
 
     return (wf, outputs)
 
@@ -2106,18 +2108,20 @@ def anatomical_init_T2(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data('T2w')
     wf.connect(node, out, T2_deoblique, 'in_file')
 
-    T2_reorient = pe.Node(interface=afni.Resample(),
-                          name=f'T2_reorient_{pipe_num}',
-                          mem_gb=0,
-                          mem_x=(0.0115, 'in_file', 't'))
-    T2_reorient.inputs.orientation = 'RPI'
-    T2_reorient.inputs.outputtype = 'NIFTI_GZ'
-
-    wf.connect(T2_deoblique, 'out_file', T2_reorient, 'in_file')
-
-    outputs = {'desc-preproc_T2w': (T2_reorient, 'out_file'),
-               'desc-reorient_T2w': (T2_reorient, 'out_file'),
-               'desc-head_T2w': (T2_reorient, 'out_file')}
+    T2_reorient = pe.Node(
+        interface=afni.Resample(),
+        name=f"T2_reorient_{pipe_num}",
+        mem_gb=0,
+        mem_x=(0.0115, "in_file", "t"),
+    )
+    T2_reorient.inputs.orientation = cfg.pipeline_setup["desired_orientation"]
+    T2_reorient.inputs.outputtype = "NIFTI_GZ"
+    wf.connect(T2_deoblique, "out_file", T2_reorient, "in_file")
+    outputs = {
+        "desc-preproc_T2w": (T2_reorient, "out_file"),
+        "desc-reorient_T2w": (T2_reorient, "out_file"),
+        "desc-head_T2w": (T2_reorient, "out_file"),
+    }
 
     return (wf, outputs)
 

CPAC/anat_preproc/lesion_preproc.py

@@ -1,8 +1,7 @@
 # -*- coding: utf-8 -*-
 
-from nipype.interfaces import afni
+from nipype.interfaces import afni, utility as util
 from CPAC.pipeline import nipype_pipeline_engine as pe
-import nipype.interfaces.utility as util
 
 
 def inverse_lesion(lesion_path):
@@ -40,9 +39,9 @@ def inverse_lesion(lesion_path):
         return lesion_out
 
 
-def create_lesion_preproc(wf_name='lesion_preproc'):
-    """
-    The main purpose of this workflow is to process lesions masks.
+def create_lesion_preproc(cfg=None, wf_name="lesion_preproc"):
+    """Process lesions masks.
+
     Lesion mask file is deobliqued and reoriented in the same way as the T1 in
     the anat_preproc function.
 
@@ -116,8 +115,10 @@ def create_lesion_preproc(wf_name='lesion_preproc'):
                               mem_gb=0,
                               mem_x=(0.0115, 'in_file', 't'))
 
-    lesion_reorient.inputs.orientation = 'RPI'
-    lesion_reorient.inputs.outputtype = 'NIFTI_GZ'
+    lesion_reorient.inputs.orientation = (
+        cfg.pipeline_setup["desired_orientation"] if cfg else "RPI"
+    )
+    lesion_reorient.inputs.outputtype = "NIFTI_GZ"
 
     preproc.connect(
         lesion_deoblique, 'out_file', lesion_reorient,

CPAC/func_preproc/func_preproc.py

@@ -534,19 +534,21 @@ def func_reorient(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data('bold')
     wf.connect(node, out, func_deoblique, 'in_file')
 
-    func_reorient = pe.Node(interface=afni_utils.Resample(),
-                            name=f'func_reorient_{pipe_num}',
-                            mem_gb=0,
-                            mem_x=(0.0115, 'in_file', 't'))
+    func_reorient = pe.Node(
+        interface=afni_utils.Resample(),
+        name=f"func_reorient_{pipe_num}",
+        mem_gb=0,
+        mem_x=(0.0115, "in_file", "t"),
+    )
 
-    func_reorient.inputs.orientation = 'RPI'
-    func_reorient.inputs.outputtype = 'NIFTI_GZ'
+    func_reorient.inputs.orientation = cfg.pipeline_setup["desired_orientation"]
+    func_reorient.inputs.outputtype = "NIFTI_GZ"
 
-    wf.connect(func_deoblique, 'out_file', func_reorient, 'in_file')
+    wf.connect(func_deoblique, "out_file", func_reorient, "in_file")
 
     outputs = {
-        'desc-preproc_bold': (func_reorient, 'out_file'),
-        'desc-reorient_bold': (func_reorient, 'out_file')
+        "desc-preproc_bold": (func_reorient, "out_file"),
+        "desc-reorient_bold": (func_reorient, "out_file"),
     }
 
     return (wf, outputs)
@@ -1129,8 +1131,8 @@ def bold_mask_anatomical_refined(wf, cfg, strat_pool, pipe_num, opt=None):
                             mem_gb=0,
                             mem_x=(0.0115, 'in_file', 't'))
 
-    func_reorient.inputs.orientation = 'RPI'
-    func_reorient.inputs.outputtype = 'NIFTI_GZ'
+    func_reorient.inputs.orientation = cfg.pipeline_setup["desired_orientation"]
+    func_reorient.inputs.outputtype = "NIFTI_GZ"
 
     wf.connect(func_deoblique, 'out_file',
                func_reorient, 'in_file')

CPAC/longitudinal_pipeline/longitudinal_workflow.py

@@ -1145,6 +1145,7 @@ def func_longitudinal_template_wf(subject_id, strat_list, config):
         resampled_template.inputs.template = template
         resampled_template.inputs.template_name = template_name
         resampled_template.inputs.tag = tag
+        resampled_template.inputs.orientation = config["desired_orientation"]
 
         strat_init.update_resource_pool({
             template_name: (resampled_template, 'resampled_template')