Source code for CPAC.reho.reho

# coding: utf-8
import os
import sys
import re
import commands
import nipype.pipeline.engine as pe
import nipype.interfaces.fsl as fsl
import nipype.interfaces.utility as util
from CPAC.reho.utils import *

[docs]def create_reho(): """ Regional Homogeneity(ReHo) approach to fMRI data analysis This workflow computes the ReHo map, z-score on map Parameters ---------- None Returns ------- reHo : workflow Regional Homogeneity Workflow Notes ----- `Source <>`_ Workflow Inputs: :: inputspec.rest_res_filt : string (existing nifti file) Input EPI 4D Volume inputspec.rest_mask : string (existing nifti file) Input Whole Brain Mask of EPI 4D Volume inputspec.cluster_size : integer For a brain voxel the number of neighbouring brain voxels to use for KCC. Possible values are 27, 19, 7. Recommended value 27 Workflow Outputs: :: outputspec.raw_reho_map : string (nifti file) outputspec.z_score : string (nifti file) ReHo Workflow Procedure: 1. Generate ReHo map from the input EPI 4D volume, EPI mask and cluster_size 2. Compute Z score of the ReHo map by subtracting mean and dividing by standard deviation Workflow Graph: .. image:: ../images/ :width: 500 Detailed Workflow Graph: .. image:: ../images/ :width: 500 References ---------- .. [1] Zang, Y., Jiang, T., Lu, Y., He, Y., Tian, L. (2004). Regional homogeneity approach to fMRI data analysis. NeuroImage, 22(1), 394, 400. doi:10.1016/j.neuroimage.2003.12.030 Examples -------- >>> from CPAC import reho >>> wf = reho.create_reho() >>> wf.inputs.inputspec.rest_res_filt = '/home/data/Project/subject/func/rest_res_filt.nii.gz' >>> wf.inputs.inputspec.rest_mask = '/home/data/Project/subject/func/rest_mask.nii.gz' >>> wf.inputs.inputspec.cluster_size = 27 >>> """ reHo = pe.Workflow(name='reHo') inputNode = pe.Node(util.IdentityInterface(fields=['cluster_size', 'rest_res_filt', 'rest_mask']), name='inputspec') outputNode = pe.Node(util.IdentityInterface(fields=['raw_reho_map']), name='outputspec') reho_imports = ['import os', 'import sys', 'import nibabel as nb', 'import numpy as np', 'from CPAC.reho.utils import f_kendall'] raw_reho_map = pe.Node(util.Function(input_names=['in_file', 'mask_file', 'cluster_size'], output_names=['out_file'], function=compute_reho, imports=reho_imports), name='reho_map') reHo.connect(inputNode, 'rest_res_filt', raw_reho_map, 'in_file') reHo.connect(inputNode, 'rest_mask', raw_reho_map, 'mask_file') reHo.connect(inputNode, 'cluster_size', raw_reho_map, 'cluster_size') reHo.connect(raw_reho_map, 'out_file', outputNode, 'raw_reho_map') return reHo