Tweaks for containers, infant stream and gems (freesurfer#864)

* [FIX] making infant stream compatible with latest niftireg (1.3.9)

* [WIP] adding binaries needed for infant stream

* [WIP] more robust cmake setings

* [WIP] cmake support for INFANT_MODULE AND MINIMAL

* [WIP] reverting niftyreg tweak now that version is correct

* [WIP] adding infant stream python reqs

* [WIP] neurodocker entrypoint

* [FIX] entrypoint

* [FIX] entrypoint perm fix

* [WIP] updating infant py reqs

* [WIP] install infant entrypoint

* [FIX] fs dir structure

* [FIX] harden against top-level files in subject dir

* [ENH] to support samseg vis

* [WIP] inital attempt at recalc script

* [WIP] cleanup and argparse

* [FIX] std:: namespace ref

* [WIP] helpful debug msg

* [WIP] comments and cleanup

CMakeLists.txt

@@ -707,6 +707,12 @@ if(INFANT_MODULE)
   add_subdirectory(sscnn_skullstripping)
 endif()
 
+if(INFANT_MODULE AND MINIMAL)
+  add_subdirectory(mri_distance_transform)
+  add_subdirectory(mri_correct_segmentations)
+  add_subdirectory(mri_morphology)
+endif()
+
 if(TKTOOLS_MODULE)
   add_subdirectory(tktools)
 endif()

distribution/average/CMakeLists.txt

@@ -44,6 +44,19 @@ if(INFANT_MODULE)
   install_tarball(CNYBCH.tar.gz DESTINATION average)
 endif()
 
+if(INFANT_MODULE AND MINIMAL)
+  install_symlinks(
+    TYPE files
+    DESTINATION average
+    lh.average.curvature.filled.buckner40.tif
+    rh.average.curvature.filled.buckner40.tif
+    lh.curvature.buckner40.filled.desikan_killiany.2010-03-25.gcs
+    rh.curvature.buckner40.filled.desikan_killiany.2010-03-25.gcs
+    lh.destrieux.simple.2009-07-29.gcs
+    rh.destrieux.simple.2009-07-29.gcs
+  )
+endif()
+
 # the following data isn't required for recon-all, but will be installed by default
 if(NOT MINIMAL)
 

gems/Executables/kvlAtlasMeshCollectionFastReferencePositionCost.cxx

@@ -239,7 +239,7 @@ ::GetValue( const ParametersType & parameters ) const
 
   // Add the components
   double  totalCost = dataCost + alphasCost + positionCost;
-  if ( isnan( totalCost ) || isinf( totalCost ) )
+  if ( std::isnan( totalCost ) || std::isinf( totalCost ) )
     {
     totalCost = itk::NumericTraits< double >::max();
     }

gems/Executables/kvlBuildAtlasMesh.cxx

@@ -145,6 +145,7 @@ int main( int argc, char** argv )
   std::vector< LabelImageType::ConstPointer >  labelImages;
   for ( int argumentNumber = 7; argumentNumber < argc; argumentNumber++ )
     {
+    std::cout << "Reading input image: " << argv[ argumentNumber ] << std::endl
     // Read the input image
     typedef itk::ImageFileReader< LabelImageType >  ReaderType;
     ReaderType::Pointer  reader = ReaderType::New();

infant/CMakeLists.txt

@@ -30,6 +30,9 @@ install_symlinks(all_c_robtemplate_affine_mean.05.01.2018.nii.gz TYPE files DEST
 install_pyscript(mri_label_fusion)
 add_subdirectory(labelfusion)
 
+# Entrypoint for containers
+install(PROGRAMS docker/infant-container-entrypoint.bash DESTINATION bin)
+
 # install external niftyreg binaries
 if(MARTINOS_BUILD)
 if(APPLE)

infant/docker/infant-container-entrypoint.bash

@@ -0,0 +1,9 @@
+#!/bin/bash
+
+# Symlink the volume_mounted model files to where FreeSurfer expects them
+mkdir -p $FREESURFER_HOME/average/sscnn_skullstripping
+ln -s $FS_INFANT_MODEL/sscnn_skullstrip/cor_sscnn.h5 $FREESURFER_HOME/average/sscnn_skullstripping/cor_sscnn.h5
+ln -s $FS_INFANT_MODEL/sscnn_skullstrip/ax_sscnn.h5 $FREESURFER_HOME/average/sscnn_skullstripping/ax_sscnn.h5
+ln -s $FS_INFANT_MODEL/sscnn_skullstrip/sag_sscnn.h5 $FREESURFER_HOME/average/sscnn_skullstripping/sag_sscnn.h5 
+
+eval "$@"

infant/docker/requirements.txt

@@ -0,0 +1,41 @@
+absl-py==0.11.0
+bleach==1.5.0
+certifi==2020.12.5
+cycler==0.10.0
+decorator==4.4.2
+h5py==2.10.0
+html5lib==0.9999999
+imageio==2.9.0
+importlib-metadata==3.4.0
+joblib==1.0.0
+Keras==2.2.2
+Keras-Applications==1.0.4
+Keras-Preprocessing==1.0.2
+kiwisolver==1.3.1
+Markdown==3.3.3
+matplotlib==3.3.3
+networkx==2.5
+nibabel==3.2.1
+numexpr==2.7.2
+numpy==1.19.5
+packaging==20.8
+Pillow==8.1.0
+protobuf==3.14.0
+psutil==5.8.0
+pyparsing==2.4.7
+python-dateutil==2.8.1
+PyWavelets==1.1.1
+PyYAML==5.3.1
+scikit-image==0.17.2
+scikit-learn==0.24.0
+scipy==1.5.3
+six==1.15.0
+sklearn==0.0
+tables==3.6.1
+tensorflow==1.5.0
+tensorflow-tensorboard==1.5.1
+threadpoolctl==2.1.0
+tifffile==2020.9.3
+typing-extensions==3.7.4.3
+Werkzeug==1.0.1
+zipp==3.4.0

infant/infant_recon_all

@@ -848,7 +848,7 @@ if !(-e $datadir/$subj/mri/transforms/talairach.auto.xfm) then
 
   set talaffine = $datadir/$subj/mri/transforms/niftyreg_affine.txt
   set cmd = (reg_aladin -ref ./${targ:t:r}.nii.gz -flo $maskedfile -aff $talaffine \
-                                     -res ${talaffine:r}.nii.gz  -voff)
+                                     -res ${talaffine:r}.nii.gz -voff)
   echo $cmd >> $LF
   echo $cmd >> $sLF
   $cmd |& tee -a $LF

python/requirements-extra.txt

@@ -16,3 +16,7 @@ pandas
 matplotlib
 transforms3d
 scikit-image==0.16.2
+
+## Samseg vis
+pyqtgraph
+PyQt5

samseg/gems_compute_binary_atlas_probs

@@ -8,7 +8,6 @@ import freesurfer as fs
 
 from freesurfer import samseg
 
-
 eps = np.finfo(float).eps
 
 parser = fs.utils.ArgumentParser()
@@ -32,7 +31,10 @@ else:
 # to call instance methods
 atlas = samseg.ProbabilisticAtlas()
 
-numberOfSubjects = len(os.listdir(args.subjects_dir))
+
+subjectList = [ pathname for pathname in os.listdir(subjects_dir) \
+                  if os.path.isdir(os.path.join(subjects_dir, pathname)) ]
+numberOfSubjects = len(subjectList)
 
 for level, meshCollectionFile in enumerate(args.mesh_collections):
 
@@ -47,8 +49,6 @@ for level, meshCollectionFile in enumerate(args.mesh_collections):
     mesh = meshCollection.reference_mesh
     numberOfNodes = mesh.point_count
 
-    #
-    subjectList = os.listdir(args.subjects_dir)
     print('Number of subjects: ' + str(len(subjectList)))
 
     # Define what we are interesting in, i.e., the label statistics of lesion
@@ -59,7 +59,7 @@ for level, meshCollectionFile in enumerate(args.mesh_collections):
         # Read the manually annotated binary segmentation for the specific subject
         segmentationImage = nib.load(os.path.join(args.segmentations_dir, subjectDir, args.segmentation_name)).get_fdata()
 
-        history = np.load(os.path.join(args.subjects_dir, subjectDir, 'history.p'), allow_pickle=True)
+        history = np.load(os.path.join(args.subjects_dir, subjectDir, 'mri/samseg/history.p'), allow_pickle=True)
 
         # Get the node positions in image voxels
         modelSpecifications = history['input']['modelSpecifications']