Segmentation Workflow#
- CPAC.seg_preproc.check_if_file_is_empty(in_file)[source]#
Raise exception if regressor fie is empty.
- Parameters
in_file (nii file (string)) – regressor file
- Returns
in_file – return same file
- Return type
string
- CPAC.seg_preproc.create_seg_preproc_antsJointLabel_method(wf_name='seg_preproc_templated_based')[source]#
Generate the subject’s cerebral spinal fluids, white matter and gray matter mask based on provided template, if selected to do so.
- Parameters
wf_name (string) – name of the workflow
- Returns
seg_preproc_templated_based – Workflow Object for Segmentation Workflow
- Return type
workflow
Notes
Workflow Inputs:
inputspec.brain : string (existing nifti file) Anatomical image(without skull) inputspec.template_brain : string (existing nifti file) Template anatomical image(without skull) inputspec.template_segmentation : string (existing nifti file) Template segmentation image(without skull)
Workflow Outputs:
outputspec.csf_mask : string (nifti file) outputs CSF mask outputspec.gm_mask : string (nifti file) outputs gray matter mask outputspec.wm_mask : string (nifti file) outputs White Matter mask
- CPAC.seg_preproc.erosion(roi_mask=None, erosion_mm=None, erosion_prop=None)[source]#
Returns eroded tissue segment mask
- Parameters
roi_mask (string) – Path to binarized segment (ROI) mask
erosion_prop (float) – Target volume ratio for erosion segment mask
- Returns
eroded_roi_mask – Path to eroded segment mask
- Return type
string
- CPAC.seg_preproc.hardcoded_antsJointLabelFusion(anatomical_brain, anatomical_brain_mask, template_brain_list, template_segmentation_list)[source]#
run antsJointLabelFusion.sh
- Parameters
anatomical_brain (string (nifti file)) – Target image to be labeled.
anatomical_brain_mask (string (nifti file)) – Target mask image
template_brain_list (list) – Atlas to be warped to target image.
template_segmentation_list (list) – Labels corresponding to atlas.
- Returns
multiatlas_Intensity (string (nifti file))
multiatlas_Labels (string (nifti file))
- CPAC.seg_preproc.mask_erosion(roi_mask=None, skullstrip_mask=None, mask_erosion_mm=None, mask_erosion_prop=None)[source]#
Returns eroded segment mask and skull-stripped brain mask
# This functionality is adapted from poldracklab/niworkflows: # https://github.com/poldracklab/niworkflows/blob/master/niworkflows/interfaces/utils.py # https://fmriprep.readthedocs.io/ # https://poldracklab.stanford.edu/ # We are temporarily maintaining our own copy for more granular control.
- Parameters
roi_mask (string) – Path to binarized segment mask
skullstrip_mask (string) – Path to skull-stripped brain mask
mask_erosion_prop (float) – Target volume ratio for skull-stripped brain mask
- Returns
output_roi_mask (string) – Path to eroded segment mask
eroded_skullstrip_mask (string) – Path to eroded skull-stripped brain mask
- CPAC.seg_preproc.pick_wm_class_0(tissue_class_files)[source]#
Returns the csf tissue class file from the list of segmented tissue class files
- Parameters
tissue_class_files (list (string)) – List of tissue class files
- Returns
file – Path to segment_seg_0.nii.gz is returned
- Return type
string
- CPAC.seg_preproc.pick_wm_class_1(tissue_class_files)[source]#
Returns the gray matter tissue class file from the list of segmented tissue class files
- Parameters
tissue_class_files (list (string)) – List of tissue class files
- Returns
file – Path to segment_seg_1.nii.gz is returned
- Return type
string
- CPAC.seg_preproc.pick_wm_class_2(tissue_class_files)[source]#
Returns the white matter tissue class file from the list of segmented tissue class files
- Parameters
tissue_class_files (list (string)) – List of tissue class files
- Returns
file – Path to segment_seg_2.nii.gz is returned
- Return type
string
- CPAC.seg_preproc.pick_wm_prob_0(probability_maps)[source]#
Returns the csf probability map from the list of segmented probability maps
- Parameters
probability_maps (list (string)) – List of Probability Maps
- Returns
file – Path to segment_prob_0.nii.gz is returned
- Return type
string
- CPAC.seg_preproc.pick_wm_prob_1(probability_maps)[source]#
Returns the gray matter probability map from the list of segmented probability maps
- Parameters
probability_maps (list (string)) – List of Probability Maps
- Returns
file – Path to segment_prob_1.nii.gz is returned
- Return type
string
- CPAC.seg_preproc.pick_wm_prob_2(probability_maps)[source]#
Returns the white matter probability map from the list of segmented probability maps
- Parameters
probability_maps (list (string)) – List of Probability Maps
- Returns
file – Path to segment_prob_2.nii.gz is returned
- Return type
string
- CPAC.seg_preproc.process_segment_map(wf_name, use_priors, use_custom_threshold, reg_tool)[source]#
This is a sub workflow used inside segmentation workflow to process probability maps obtained in segmentation. Steps include overlapping of the prior tissue with probability maps, thresholding and binarizing it and creating a mask that is used in further analysis.
- Parameters
wf_name (string) – Workflow Name
use_priors (boolean) – Whether or not to use template-space tissue priors to further refine the resulting segmentation tissue masks.
use_threshold (list) – Choose threshold to further refine the resulting segmentation tissue masks.
use_erosion (boolean) – Whether or not to erode the resulting segmentation tissue masks.
use_ants (boolean) – Whether or not to use ANTs or FSL for transform application.
- Returns
preproc – Workflow Object for process_segment_map Workflow
- Return type
workflow
Notes
Workflow Inputs:
inputspec.brain : string (existing nifti file) Anatomical image(without skull) inputspec.standard2highres_mat : string (existing affine transformation .mat file) path to transformation matrix from mni space to anatomical space inputspec.threshold : float threshold value inputspec.tissue_prior : string (existing nifti file) path to FSL Standard Tissue prior image inputspec.probability_tissue_map : string (nifti file) tissue Probability map obtained from fsl FAST
Workflow Outputs:
outputspec.segment_mni2t1 : string (nifti file) path to output CSF prior template(in MNI space) registered to anatomical space outputspec.segment_combo : string (nifti file) path to output image containing overlap between csf probability map and segment_mni2t1 outputspec.segment_thresh : string (nifti file) path to output image after Thresholding segment_combo outputspec.segment_bin : string (nifti file) path to output image after binarizing segment_thresh outputspec.segment_erosion : string (nifti file) path to output image after eroding segment_bin outputspec.segment_mask : string (nifti file) path to output image after masking segment_combo with its tissue prior in t1 space
Order of commands:
Register tissue prior in MNI space to t1 space.
Threshold segment probability map
Binarize threshed segment probability map
Erose binarized segment mask
Generate segment mask, by applying tissue prior in t1 space to thresholded binarized segment probability map
Error
Unable to execute python code at exec.py:31:
process_segment_map() takes 4 positional arguments but 5 were given
High Level Graph:
Detailed Graph: