Merge pull request #41 from mgxd/rel/0.0.3

REL: 0.0.3

Author: mgxd

CHANGES.md

@@ -1,5 +1,13 @@
 ## Changelog
 
+0.0.3 (March 17, 2021)
+-----------------------
+- Adds functional processing to the workflow
+  - minus SDC and fine-grain subcortical CIFTI generation
+- Revision of T1w/T2w templates when multiple runs are detected
+- Modularization of T1w-T2w coregistration, with increased robustness
+- Removed of UNCInfant for a default output space
+
 0.0.2 (Feb 18, 2021)
 --------------------
 - Improved robustness of structural coregistration

Dockerfile

@@ -205,14 +205,13 @@ RUN python -c "from matplotlib import font_manager" && \
 RUN pip install --no-cache-dir templateflow && \
     rm -rf $HOME/.cache/pip
 
-RUN python -c "from templateflow import api as tfapi; \
-               tfapi.get('MNIInfant', cohort=1); \
-               tfapi.get('UNCInfant', cohort=1);"
-
 WORKDIR /src
 COPY . nibabies
 WORKDIR /src/nibabies
 
+# fetch the necessary templateflow files
+RUN python scripts/fetch_templates.py
+
 RUN pip install --no-cache-dir -e .[all] && \
     rm -rf $HOME/.cache/pip
 

nibabies/workflows/anatomical/base.py

@@ -74,7 +74,6 @@ def init_infant_anat_wf(
     surfaces
         GIFTI surfaces (gray/white boundary, midthickness, pial, inflated)
     """
-    from nipype.interfaces.base import Undefined
     from nipype.interfaces.ants.base import Info as ANTsInfo
     from smriprep.workflows.outputs import init_anat_derivatives_wf
 

nibabies/workflows/bold/confounds.py

@@ -218,7 +218,8 @@ def init_bold_confs_wf(
         ACompCor(components_file='acompcor.tsv', header_prefix='a_comp_cor_', pre_filter='cosine',
                  save_pre_filter=True, save_metadata=True, mask_names=['CSF', 'WM', 'combined'],
                  merge_method='none', failure_mode='NaN'),
-        name="acompcor", mem_gb=8, nprocs=6)  # TODO: Lessen expensive restrictions
+        name="acompcor", mem_gb=mem_gb, n_procs=6  # TODO: Lessen expensive restrictions
+    )
 
     tcompcor = pe.Node(
         TCompCor(components_file='tcompcor.tsv', header_prefix='t_comp_cor_', pre_filter='cosine',
@@ -245,8 +246,10 @@ def init_bold_confs_wf(
     ]
     merge_rois = pe.Node(niu.Merge(3, ravel_inputs=True), name='merge_rois',
                          run_without_submitting=True)
-    signals = pe.Node(SignalExtraction(class_labels=signals_class_labels),
-                      name="signals", mem_gb=8, n_procs=6)  # TODO: Lessen expensive restrictions
+    signals = pe.Node(
+        SignalExtraction(class_labels=signals_class_labels),
+        name="signals", mem_gb=mem_gb, n_procs=6  # TODO: Lessen expensive restrictions
+    )
 
     # Arrange confounds
     add_dvars_header = pe.Node(
@@ -293,8 +296,10 @@ def init_bold_confs_wf(
     # Generate reportlet (ROIs)
     mrg_compcor = pe.Node(niu.Merge(2, ravel_inputs=True),
                           name='mrg_compcor', run_without_submitting=True)
-    rois_plot = pe.Node(ROIsPlot(colors=['b', 'magenta'], generate_report=True),
-                        name='rois_plot', mem_gb=4)  # TODO: Lessen expensive restrictions
+    rois_plot = pe.Node(
+        ROIsPlot(colors=['b', 'magenta'], generate_report=True),
+        name='rois_plot', mem_gb=mem_gb, n_procs=6  # 4 TODO: Lessen expensive restrictions
+    )
 
     ds_report_bold_rois = pe.Node(
         DerivativesDataSink(desc='rois', datatype="figures", dismiss_entities=("echo",)),
@@ -453,7 +458,6 @@ def init_carpetplot_wf(mem_gb, metadata, cifti_output, name="bold_carpet_wf"):
 
     """
     from niworkflows.engine.workflows import LiterateWorkflow as Workflow
-    from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 
     inputnode = pe.Node(niu.IdentityInterface(
         fields=['bold', 'bold_mask', 'confounds_file',

nibabies/workflows/bold/resampling.py

@@ -339,7 +339,7 @@ def init_bold_std_trans_wf(
         name='bold_to_std_transform', mem_gb=mem_gb * 3 * omp_nthreads, n_procs=omp_nthreads)
 
     merge = pe.Node(Merge(compress=use_compression), name='merge',
-                    mem_gb=3)  # TODO: Lessen expensive restrictions
+                    mem_gb=mem_gb * 3)  # TODO: Lessen expensive restrictions
 
     # Generate a reference on the target standard space
     # TODO: Replace with masking interface?

scripts/fetch_templates.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python
+
+"Pre-emptive caching of commonly used TemplateFlow templates"
+import templateflow.api as tf
+
+
+def fetch_MNI6():
+    """
+    Expected templates:
+
+    tpl-MNI152NLin6Asym/tpl-MNI152NLin6Asym_res-01_T1w.nii.gz
+    tpl-MNI152NLin6Asym/tpl-MNI152NLin6Asym_res-02_T1w.nii.gz
+    tpl-MNI152NLin6Asym/tpl-MNI152NLin6Asym_res-01_desc-brain_mask.nii.gz
+    tpl-MNI152NLin6Asym/tpl-MNI152NLin6Asym_res-02_desc-brain_mask.nii.gz
+    tpl-MNI152NLin6Asym/tpl-MNI152NLin6Asym_res-02_atlas-HCP_dseg.nii.gz
+    """
+    template = 'MNI152NLin6Asym'
+
+    tf.get(template, resolution=(1, 2), desc=None, suffix='T1w')
+    tf.get(template, resolution=(1, 2), desc='brain', suffix='mask')
+    # CIFTI
+    tf.get(template, resolution=2, atlas='HCP', suffix='dseg')
+
+
+def fetch_UNCInfant():
+    """
+    Expected templates:
+
+    tpl-UNCInfant/cohort-1/tpl-UNCInfant_cohort-1_T1w.nii.gz
+    tpl-UNCInfant/cohort-1/tpl-UNCInfant_cohort-1_label-brain_probseg.nii.gz
+    tpl-UNCInfant/cohort-1/tpl-UNCInfant_cohort-1_label-brain_mask.nii.gz
+    tpl-UNCInfant/cohort-1/tpl-UNCInfant_cohort-1_label-BrainCerebellumExtraction_mask.nii.gz
+    """
+    template = "UNCInfant"
+
+    tf.get(template, cohort=1, desc=None, suffix='T1w')
+    tf.get(template, cohort=1, label='brain', suffix='probseg')
+    tf.get(template, cohort=1, label='brain', suffix='mask')
+    tf.get(template, cohort=1, label='BrainCerebellumExtraction', suffix='mask')
+
+
+def fetch_fsaverage():
+    """
+    Expected templates:
+
+    tpl-fsaverage/tpl-fsaverage_hemi-L_den-164k_desc-std_sphere.surf.gii
+    tpl-fsaverage/tpl-fsaverage_hemi-R_den-164k_desc-std_sphere.surf.gii
+    tpl-fsaverage/tpl-fsaverage_hemi-L_den-164k_desc-vaavg_midthickness.shape.gii
+    tpl-fsaverage/tpl-fsaverage_hemi-R_den-164k_desc-vaavg_midthickness.shape.gii
+    """
+    template = 'fsaverage'
+
+    tf.get(template, density='164k', desc='std', suffix='sphere')
+    tf.get(template, density='164k', desc='vaavg', suffix='midthickness')
+
+
+def fetch_fsLR():
+    """
+    Expected templates:
+
+    tpl-fsLR/tpl-fsLR_hemi-L_den-32k_desc-nomedialwall_dparc.label.gii
+    tpl-fsLR/tpl-fsLR_hemi-L_den-32k_desc-vaavg_midthickness.shape.gii
+    tpl-fsLR/tpl-fsLR_hemi-L_den-32k_sphere.surf.gii
+    tpl-fsLR/tpl-fsLR_hemi-R_den-32k_desc-nomedialwall_dparc.label.gii
+    tpl-fsLR/tpl-fsLR_hemi-R_den-32k_desc-vaavg_midthickness.shape.gii
+    tpl-fsLR/tpl-fsLR_hemi-R_den-32k_sphere.surf.gii
+    tpl-fsLR/tpl-fsLR_space-fsaverage_hemi-L_den-32k_sphere.surf.gii
+    tpl-fsLR/tpl-fsLR_space-fsaverage_hemi-R_den-32k_sphere.surf.gii
+    """
+    tf.get('fsLR', density='32k')
+
+
+def main():
+    fetch_MNI6()
+    fetch_UNCInfant()
+    fetch_fsaverage()
+    fetch_fsLR()
+
+
+if __name__ == "__main__":
+    main()