def qc_epi_segmentation(wf, cfg, strat_pool, pipe_num, opt=None): ''' {"name": "qc_epi_segmentation", "config": ["pipeline_setup", "output_directory"], "switch": ["generate_quality_control_images"], "option_key": "None", "option_val": "None", "inputs": [("desc-brain_bold", ["space-bold_label-CSF_desc-preproc_mask", "space-bold_label-CSF_mask"], ["space-bold_label-WM_desc-preproc_mask", "space-bold_label-WM_mask"], ["space-bold_label-GM_desc-preproc_mask", "space-bold_label-GM_mask"])], "outputs": ["epi-dseg-axial-qc", "epi-dseg-sagittal-qc"]} ''' # make QC montages for CSF WM GM montage_csf_gm_wm = create_montage_gm_wm_csf( f'montage_csf_gm_wm_{pipe_num}', 'montage_csf_gm_wm') node, out = strat_pool.get_data('desc-brain_bold') wf.connect(node, out, montage_csf_gm_wm, 'inputspec.underlay') node, out = strat_pool.get_data([ 'space-bold_label-CSF_desc-preproc_mask', 'space-bold_label-CSF_mask' ]) wf.connect(node, out, montage_csf_gm_wm, 'inputspec.overlay_csf') node, out = strat_pool.get_data( ['space-bold_label-WM_desc-preproc_mask', 'space-bold_label-WM_mask']) wf.connect(node, out, montage_csf_gm_wm, 'inputspec.overlay_wm') node, out = strat_pool.get_data( ['space-bold_label-GM_desc-preproc_mask', 'space-bold_label-GM_mask']) wf.connect(node, out, montage_csf_gm_wm, 'inputspec.overlay_gm') outputs = { 'epi-dseg-axial-qc': (montage_csf_gm_wm, 'outputspec.axial_png'), 'epi-dseg-sagittal-qc': (montage_csf_gm_wm, 'outputspec.sagittal_png') } return (wf, outputs)
def create_qc_workflow(workflow, c, strategies, qc_outputs): qc_montage_id_a = {} qc_montage_id_s = {} qc_plot_id = {} qc_hist_id = {} for num_strat, strat in enumerate(strategies): nodes = strat.get_nodes_names() if 'functional_preprocessed' in strat: preproc, out_file = strat['functional_preprocessed'] brain_mask, mask_file = strat['functional_brain_mask'] func_to_anat_xfm, xfm_file = strat['functional_to_anat_linear_xfm'] anat_ref, ref_file = strat['anatomical_brain'] mfa, mfa_file = strat['mean_functional_in_anat'] # make SNR plot qc_workflow = create_qc_snr('qc_snr_{0}'.format(num_strat)) workflow.connect(preproc, out_file, qc_workflow, 'inputspec.functional_preprocessed') workflow.connect(brain_mask, mask_file, qc_workflow, 'inputspec.functional_brain_mask') workflow.connect(func_to_anat_xfm, xfm_file, qc_workflow, 'inputspec.functional_to_anat_linear_xfm') workflow.connect(anat_ref, ref_file, qc_workflow, 'inputspec.anatomical_brain') workflow.connect(mfa, mfa_file, qc_workflow, 'inputspec.mean_functional_in_anat') strat.update_resource_pool({ 'qc___snr_a': (qc_workflow, 'outputspec.snr_axial_image'), 'qc___snr_s': (qc_workflow, 'outputspec.snr_sagittal_image'), 'qc___snr_hist': (qc_workflow, 'outputspec.snr_histogram_image'), 'qc___snr_val': (qc_workflow, 'outputspec.snr_mean') }) if not 0 in qc_montage_id_a: qc_montage_id_a[0] = 'snr_a' qc_montage_id_s[0] = 'snr_s' qc_hist_id[0] = 'snr_hist' # make motion parameters plot mov_param, out_file = strat['movement_parameters'] qc_workflow = create_qc_motion('qc_motion_{0}'.format(num_strat)) workflow.connect(mov_param, out_file, qc_workflow, 'inputspec.motion_parameters') strat.update_resource_pool({ 'qc___movement_trans_plot': (qc_workflow, 'outputspec.motion_translation_plot'), 'qc___movement_rot_plot': (qc_workflow, 'outputspec.motion_rotation_plot') }) if not 1 in qc_plot_id: qc_plot_id[1] = 'movement_trans_plot' if not 2 in qc_plot_id: qc_plot_id[2] = 'movement_rot_plot' # make FD plot and volumes removed if ('gen_motion_stats' in nodes or 'gen_motion_stats_before_stc' in nodes) and 1 in c.runNuisance: fd, out_file = strat['frame_wise_displacement_jenkinson'] qc_workflow = create_qc_fd('qc_fd_{0}'.format(num_strat)) workflow.connect(fd, out_file, qc_workflow, 'inputspec.fd') strat.update_resource_pool({ 'qc___fd_plot': (qc_workflow, 'outputspec.fd_histogram_plot') }) if not 3 in qc_plot_id: qc_plot_id[3] = 'fd_plot' # make QC montages for Skull Stripping Visualization anat_underlay, out_file = strat['anatomical_brain'] skull, out_file_s = strat['anatomical_reorient'] qc_workflow = create_qc_skullstrip( 'qc_skullstrip_{0}'.format(num_strat)) workflow.connect(anat_underlay, out_file, qc_workflow, 'inputspec.anatomical_brain') workflow.connect(skull, out_file_s, qc_workflow, 'inputspec.anatomical_reorient') strat.update_resource_pool({ 'qc___skullstrip_vis_a': (qc_workflow, 'outputspec.axial_image'), 'qc___skullstrip_vis_s': (qc_workflow, 'outputspec.sagittal_image') }) if not 4 in qc_montage_id_a: qc_montage_id_a[4] = 'skullstrip_vis_a' qc_montage_id_s[4] = 'skullstrip_vis_s' if 'anatomical_to_standard' in strat: # make QC montages for mni normalized anatomical image mni_anat_underlay, out_file = strat['anatomical_to_standard'] montage_mni_anat = create_montage( 'montage_mni_anat_{0}'.format(num_strat), 'red', 'mni_anat') workflow.connect(mni_anat_underlay, out_file, montage_mni_anat, 'inputspec.underlay') template_brain_for_anat, out_file = strat[ 'template_brain_for_anat'] anat_template_edge = pe.Node( Function(input_names=['in_file'], output_names=['out_file'], function=afni_Edge3, as_module=True), name='anat_template_edge_{0}'.format(num_strat)) workflow.connect(template_brain_for_anat, out_file, anat_template_edge, 'in_file') workflow.connect(anat_template_edge, 'out_file', montage_mni_anat, 'inputspec.overlay') strat.update_resource_pool({ 'qc___mni_normalized_anatomical_a': (montage_mni_anat, 'outputspec.axial_png'), 'qc___mni_normalized_anatomical_s': (montage_mni_anat, 'outputspec.sagittal_png') }) if not 5 in qc_montage_id_a: qc_montage_id_a[5] = 'mni_normalized_anatomical_a' qc_montage_id_s[5] = 'mni_normalized_anatomical_s' # make QC montages for CSF WM GM if 'seg_preproc' in nodes: anat_underlay, out_file_anat = strat['anatomical_brain'] csf_overlay, out_file_csf = strat['anatomical_csf_mask'] wm_overlay, out_file_wm = strat['anatomical_wm_mask'] gm_overlay, out_file_gm = strat['anatomical_gm_mask'] montage_csf_gm_wm = create_montage_gm_wm_csf( 'montage_csf_gm_wm_%d' % num_strat, 'montage_csf_gm_wm') workflow.connect(anat_underlay, out_file_anat, montage_csf_gm_wm, 'inputspec.underlay') workflow.connect(csf_overlay, out_file_csf, montage_csf_gm_wm, 'inputspec.overlay_csf') workflow.connect(wm_overlay, out_file_wm, montage_csf_gm_wm, 'inputspec.overlay_wm') workflow.connect(gm_overlay, out_file_gm, montage_csf_gm_wm, 'inputspec.overlay_gm') strat.update_resource_pool({ 'qc___csf_gm_wm_a': (montage_csf_gm_wm, 'outputspec.axial_png'), 'qc___csf_gm_wm_s': (montage_csf_gm_wm, 'outputspec.sagittal_png') }) if not 7 in qc_montage_id_a: qc_montage_id_a[7] = 'csf_gm_wm_a' qc_montage_id_s[7] = 'csf_gm_wm_s' if 'functional_preprocessed' in strat: preproc, out_file_preproc = strat['functional_to_standard'] mean_preproc, out_file_mean_preproc = strat[ 'mean_functional_to_standard'] # make QC Carpet plot carpet_seg = create_qc_carpet('carpet_seg_%d' % num_strat, 'carpet_seg') workflow.connect(preproc, out_file_preproc, carpet_seg, 'inputspec.functional_to_standard') workflow.connect(mean_preproc, out_file_mean_preproc, carpet_seg, 'inputspec.mean_functional_to_standard') workflow.connect(c.PRIORS_GRAY, 'local_path', carpet_seg, 'inputspec.anatomical_gm_mask') workflow.connect(c.PRIORS_WHITE, 'local_path', carpet_seg, 'inputspec.anatomical_wm_mask') workflow.connect(c.PRIORS_CSF, 'local_path', carpet_seg, 'inputspec.anatomical_csf_mask') strat.update_resource_pool({ 'qc___carpet': (carpet_seg, 'outputspec.carpet_plot'), }) if not 8 in qc_plot_id: qc_plot_id[8] = 'carpet' if 'functional_preprocessed' in strat: # make QC montage for Mean Functional in T1 with T1 edge anat, out_file = strat['anatomical_brain'] m_f_a, out_file_mfa = strat['mean_functional_in_anat'] anat_edge = pe.Node(Function(input_names=['in_file'], output_names=['out_file'], function=afni_Edge3, as_module=True), name='anat_edge_%d' % num_strat) montage_anat = create_montage('montage_anat_%d' % num_strat, 'red', 't1_edge_on_mean_func_in_t1') workflow.connect(anat, out_file, anat_edge, 'in_file') workflow.connect(anat_edge, 'out_file', montage_anat, 'inputspec.overlay') workflow.connect(m_f_a, out_file_mfa, montage_anat, 'inputspec.underlay') strat.update_resource_pool({ 'qc___mean_func_with_t1_edge_a': (montage_anat, 'outputspec.axial_png'), 'qc___mean_func_with_t1_edge_s': (montage_anat, 'outputspec.sagittal_png') }) if not 9 in qc_montage_id_a: qc_montage_id_a[9] = 'mean_func_with_t1_edge_a' qc_montage_id_s[9] = 'mean_func_with_t1_edge_s' # make QC montage for Mean Functional in MNI with MNI edge m_f_i, out_file = strat['mean_functional_to_standard'] montage_mfi = create_montage('montage_mfi_%d' % num_strat, 'red', 'MNI_edge_on_mean_func_mni') workflow.connect(m_f_i, out_file, montage_mfi, 'inputspec.underlay') template_brain_for_func, out_file = strat[ 'template_brain_for_func_preproc'] func_template_edge = pe.Node( Function(input_names=['in_file'], output_names=['out_file'], function=afni_Edge3, as_module=True), name='func_template_edge_{0}'.format(num_strat)) workflow.connect(template_brain_for_func, out_file, func_template_edge, 'in_file') workflow.connect(func_template_edge, 'out_file', montage_mfi, 'inputspec.overlay') strat.update_resource_pool({ 'qc___mean_func_with_mni_edge_a': (montage_mfi, 'outputspec.axial_png'), 'qc___mean_func_with_mni_edge_s': (montage_mfi, 'outputspec.sagittal_png') }) if not 10 in qc_montage_id_a: qc_montage_id_a[10] = 'mean_func_with_mni_edge_a' qc_montage_id_s[10] = 'mean_func_with_mni_edge_s' # Link all the derivatives to the QC pages idx = 11 rp = strat.get_resource_pool() for key in sorted(rp.keys()): # qc_outputs is from the outputs CSV if key in qc_outputs: qa_montages(workflow, c, strat, num_strat, qc_montage_id_a, qc_montage_id_s, qc_hist_id, key, idx) idx += 1 return qc_montage_id_a, qc_montage_id_s, qc_hist_id, qc_plot_id
def create_qc_workflow(workflow, c, strategies, qc_outputs): qc_montage_id_a = {} qc_montage_id_s = {} qc_plot_id = {} qc_hist_id = {} for num_strat, strat in enumerate(strategies): nodes = strat.get_nodes_names() preproc, out_file = strat['functional_preprocessed'] brain_mask, mask_file = strat['functional_brain_mask'] func_to_anat_xfm, xfm_file = strat['functional_to_anat_linear_xfm'] anat_ref, ref_file = strat['anatomical_brain'] mfa, mfa_file = strat['mean_functional_in_anat'] # make SNR plot qc_workflow = create_qc_snr('qc_snr_{0}'.format(num_strat)) workflow.connect(preproc, out_file, qc_workflow, 'inputspec.functional_preprocessed') workflow.connect(brain_mask, mask_file, qc_workflow, 'inputspec.functional_brain_mask') workflow.connect(func_to_anat_xfm, xfm_file, qc_workflow, 'inputspec.functional_to_anat_linear_xfm') workflow.connect(anat_ref, ref_file, qc_workflow, 'inputspec.anatomical_brain') workflow.connect(mfa, mfa_file, qc_workflow, 'inputspec.mean_functional_in_anat') strat.update_resource_pool({ 'qc___snr_a': (qc_workflow, 'outputspec.snr_axial_image'), 'qc___snr_s': (qc_workflow, 'outputspec.snr_sagittal_image'), 'qc___snr_hist': (qc_workflow, 'outputspec.snr_histogram_image'), 'qc___snr_val': (qc_workflow, 'outputspec.snr_mean') }) if not 3 in qc_montage_id_a: qc_montage_id_a[3] = 'snr_a' qc_montage_id_s[3] = 'snr_s' qc_hist_id[3] = 'snr_hist' # make motion parameters plot mov_param, out_file = strat['movement_parameters'] qc_workflow = create_qc_motion('qc_motion_{0}'.format(num_strat)) workflow.connect(mov_param, out_file, qc_workflow, 'inputspec.motion_parameters') strat.update_resource_pool({ 'qc___movement_trans_plot': (qc_workflow, 'outputspec.motion_translation_plot'), 'qc___movement_rot_plot': (qc_workflow, 'outputspec.motion_rotation_plot') }) if not 6 in qc_plot_id: qc_plot_id[6] = 'movement_trans_plot' if not 7 in qc_plot_id: qc_plot_id[7] = 'movement_rot_plot' # make FD plot and volumes removed if 'gen_motion_stats' in nodes and 1 in c.runNuisance: if c.fdCalc == 'Power': fd, out_file = strat['frame_wise_displacement_power'] else: fd, out_file = strat['frame_wise_displacement_jenkinson'] qc_workflow = create_qc_fd('qc_fd_{0}'.format(num_strat)) workflow.connect(fd, out_file, qc_workflow, 'inputspec.fd') if "De-Spiking" in c.runMotionSpike: excluded, out_file_ex = strat['despiking_frames_excluded'] workflow.connect(excluded, out_file_ex, qc_workflow, 'inputspec.excluded_volumes') elif "Scrubbing" in c.runMotionSpike: excluded, out_file_ex = strat['scrubbing_frames_excluded'] workflow.connect(excluded, out_file_ex, qc_workflow, 'inputspec.excluded_volumes') strat.update_resource_pool({ 'qc___fd_plot': (qc_workflow, 'outputspec.fd_histogram_plot') }) if not 8 in qc_plot_id: qc_plot_id[8] = 'fd_plot' # make QC montages for Skull Stripping Visualization anat_underlay, out_file = strat['anatomical_brain'] skull, out_file_s = strat['anatomical_reorient'] qc_workflow = create_qc_skullstrip( 'qc_skullstrip_{0}'.format(num_strat)) workflow.connect(anat_underlay, out_file, qc_workflow, 'inputspec.anatomical_brain') workflow.connect(skull, out_file_s, qc_workflow, 'inputspec.anatomical_reorient') strat.update_resource_pool({ 'qc___skullstrip_vis_a': (qc_workflow, 'outputspec.axial_image'), 'qc___skullstrip_vis_s': (qc_workflow, 'outputspec.sagittal_image') }) if not 1 in qc_montage_id_a: qc_montage_id_a[1] = 'skullstrip_vis_a' qc_montage_id_s[1] = 'skullstrip_vis_s' # make QC montages for mni normalized anatomical image mni_anat_underlay, out_file = strat['mean_functional_in_anat'] montage_mni_anat = create_montage( 'montage_mni_anat_{0}'.format(num_strat), 'red', 'mni_anat') workflow.connect(mni_anat_underlay, out_file, montage_mni_anat, 'inputspec.underlay') montage_mni_anat.inputs.inputspec.overlay = os.path.abspath( p.resource_filename( 'CPAC', 'resources/templates/MNI152_Edge_AllTissues.nii.gz')) strat.update_resource_pool({ 'qc___mni_normalized_anatomical_a': (montage_mni_anat, 'outputspec.axial_png'), 'qc___mni_normalized_anatomical_s': (montage_mni_anat, 'outputspec.sagittal_png') }) if not 6 in qc_montage_id_a: qc_montage_id_a[6] = 'mni_normalized_anatomical_a' qc_montage_id_s[6] = 'mni_normalized_anatomical_s' # make QC montages for CSF WM GM if 'seg_preproc' in nodes: anat_underlay, out_file = strat['anatomical_brain'] csf_overlay, out_file_csf = strat['anatomical_csf_mask'] wm_overlay, out_file_wm = strat['anatomical_wm_mask'] gm_overlay, out_file_gm = strat['anatomical_gm_mask'] montage_csf_gm_wm = create_montage_gm_wm_csf( 'montage_csf_gm_wm_%d' % num_strat, 'montage_csf_gm_wm') workflow.connect(anat_underlay, out_file, montage_csf_gm_wm, 'inputspec.underlay') workflow.connect(csf_overlay, out_file_csf, montage_csf_gm_wm, 'inputspec.overlay_csf') workflow.connect(wm_overlay, out_file_wm, montage_csf_gm_wm, 'inputspec.overlay_wm') workflow.connect(gm_overlay, out_file_gm, montage_csf_gm_wm, 'inputspec.overlay_gm') strat.update_resource_pool({ 'qc___csf_gm_wm_a': (montage_csf_gm_wm, 'outputspec.axial_png'), 'qc___csf_gm_wm_s': (montage_csf_gm_wm, 'outputspec.sagittal_png') }) if not 2 in qc_montage_id_a: qc_montage_id_a[2] = 'csf_gm_wm_a' qc_montage_id_s[2] = 'csf_gm_wm_s' # make QC montage for Mean Functional in T1 with T1 edge anat, out_file = strat['anatomical_brain'] m_f_a, out_file_mfa = strat['mean_functional_in_anat'] anat_edge = pe.Node(Function(input_names=['in_file'], output_names=['out_file'], function=afni_Edge3, as_module=True), name='anat_edge_%d' % num_strat) montage_anat = create_montage('montage_anat_%d' % num_strat, 'red', 't1_edge_on_mean_func_in_t1') workflow.connect(anat, out_file, anat_edge, 'in_file') workflow.connect(anat_edge, 'out_file', montage_anat, 'inputspec.overlay') workflow.connect(m_f_a, out_file_mfa, montage_anat, 'inputspec.underlay') strat.update_resource_pool({ 'qc___mean_func_with_t1_edge_a': (montage_anat, 'outputspec.axial_png'), 'qc___mean_func_with_t1_edge_s': (montage_anat, 'outputspec.sagittal_png') }) if not 4 in qc_montage_id_a: qc_montage_id_a[4] = 'mean_func_with_t1_edge_a' qc_montage_id_s[4] = 'mean_func_with_t1_edge_s' # make QC montage for Mean Functional in MNI with MNI edge m_f_i, out_file = strat['mean_functional_to_standard'] montage_mfi = create_montage('montage_mfi_%d' % num_strat, 'red', 'MNI_edge_on_mean_func_mni') workflow.connect(m_f_i, out_file, montage_mfi, 'inputspec.underlay') montage_mfi.inputs.inputspec.overlay = os.path.abspath( p.resource_filename( 'CPAC', 'resources/templates/MNI152_Edge_AllTissues.nii.gz')) strat.update_resource_pool({ 'qc___mean_func_with_mni_edge_a': (montage_mfi, 'outputspec.axial_png'), 'qc___mean_func_with_mni_edge_s': (montage_mfi, 'outputspec.sagittal_png') }) if not 5 in qc_montage_id_a: qc_montage_id_a[5] = 'mean_func_with_mni_edge_a' qc_montage_id_s[5] = 'mean_func_with_mni_edge_s' # Link all the derivatives to the QC pages idx = 7 rp = strat.get_resource_pool() for key in sorted(rp.keys()): # qc_outputs is from the outputs CSV if key in qc_outputs: qa_montages(workflow, c, strat, num_strat, qc_montage_id_a, qc_montage_id_s, qc_hist_id, key, idx) idx += 1 return qc_montage_id_a, qc_montage_id_s, qc_hist_id, qc_plot_id
def create_qc_workflow(workflow, c, strategies, qc_outputs): qc_montage_id_a = {} qc_montage_id_s = {} qc_plot_id = {} qc_hist_id = {} for num_strat, strat in enumerate(strategies): nodes = strat.get_nodes_names() if 'functional_preprocessed' in strat: preproc, out_file = strat['functional_preprocessed'] brain_mask, mask_file = strat['functional_brain_mask'] func_to_anat_xfm, xfm_file = strat['functional_to_anat_linear_xfm'] anat_ref, ref_file = strat['anatomical_brain'] mfa, mfa_file = strat['mean_functional_in_anat'] # make SNR plot qc_workflow = create_qc_snr('qc_snr_{0}'.format(num_strat)) workflow.connect(preproc, out_file, qc_workflow, 'inputspec.functional_preprocessed') workflow.connect(brain_mask, mask_file, qc_workflow, 'inputspec.functional_brain_mask') workflow.connect(func_to_anat_xfm, xfm_file, qc_workflow, 'inputspec.functional_to_anat_linear_xfm') workflow.connect(anat_ref, ref_file, qc_workflow, 'inputspec.anatomical_brain') workflow.connect(mfa, mfa_file, qc_workflow, 'inputspec.mean_functional_in_anat') strat.update_resource_pool({ 'qc___snr_a': (qc_workflow, 'outputspec.snr_axial_image'), 'qc___snr_s': (qc_workflow, 'outputspec.snr_sagittal_image'), 'qc___snr_hist': (qc_workflow, 'outputspec.snr_histogram_image'), 'qc___snr_val': (qc_workflow, 'outputspec.snr_mean') }) if not 3 in qc_montage_id_a: qc_montage_id_a[3] = 'snr_a' qc_montage_id_s[3] = 'snr_s' qc_hist_id[3] = 'snr_hist' # make motion parameters plot mov_param, out_file = strat['movement_parameters'] qc_workflow = create_qc_motion('qc_motion_{0}'.format(num_strat)) workflow.connect(mov_param, out_file, qc_workflow, 'inputspec.motion_parameters') strat.update_resource_pool({ 'qc___movement_trans_plot': (qc_workflow, 'outputspec.motion_translation_plot'), 'qc___movement_rot_plot': (qc_workflow, 'outputspec.motion_rotation_plot') }) if not 6 in qc_plot_id: qc_plot_id[6] = 'movement_trans_plot' if not 7 in qc_plot_id: qc_plot_id[7] = 'movement_rot_plot' # make FD plot and volumes removed if 'gen_motion_stats' in nodes and 1 in c.runNuisance: fd, out_file = strat['frame_wise_displacement_jenkinson'] qc_workflow = create_qc_fd('qc_fd_{0}'.format(num_strat)) workflow.connect(fd, out_file, qc_workflow, 'inputspec.fd') strat.update_resource_pool({ 'qc___fd_plot': (qc_workflow, 'outputspec.fd_histogram_plot') }) if not 8 in qc_plot_id: qc_plot_id[8] = 'fd_plot' # make QC montages for Skull Stripping Visualization anat_underlay, out_file = strat['anatomical_brain'] skull, out_file_s = strat['anatomical_reorient'] qc_workflow = create_qc_skullstrip( 'qc_skullstrip_{0}'.format(num_strat) ) workflow.connect(anat_underlay, out_file, qc_workflow, 'inputspec.anatomical_brain') workflow.connect(skull, out_file_s, qc_workflow, 'inputspec.anatomical_reorient') strat.update_resource_pool({ 'qc___skullstrip_vis_a': (qc_workflow, 'outputspec.axial_image'), 'qc___skullstrip_vis_s': (qc_workflow, 'outputspec.sagittal_image') }) if not 1 in qc_montage_id_a: qc_montage_id_a[1] = 'skullstrip_vis_a' qc_montage_id_s[1] = 'skullstrip_vis_s' if 'functional_preprocessed' in strat: # make QC montages for mni normalized anatomical image mni_anat_underlay, out_file = strat['mean_functional_in_anat'] montage_mni_anat = create_montage('montage_mni_anat_{0}'.format(num_strat), 'red', 'mni_anat') workflow.connect(mni_anat_underlay, out_file, montage_mni_anat, 'inputspec.underlay') montage_mni_anat.inputs.inputspec.overlay = os.path.abspath( p.resource_filename( 'CPAC', 'resources/templates/MNI152_Edge_AllTissues.nii.gz' ) ) strat.update_resource_pool({'qc___mni_normalized_anatomical_a': (montage_mni_anat, 'outputspec.axial_png'), 'qc___mni_normalized_anatomical_s': (montage_mni_anat, 'outputspec.sagittal_png')}) if not 6 in qc_montage_id_a: qc_montage_id_a[6] = 'mni_normalized_anatomical_a' qc_montage_id_s[6] = 'mni_normalized_anatomical_s' # make QC montages for CSF WM GM if 'seg_preproc' in nodes: anat_underlay, out_file_anat = strat['anatomical_brain'] csf_overlay, out_file_csf = strat['anatomical_csf_mask'] wm_overlay, out_file_wm = strat['anatomical_wm_mask'] gm_overlay, out_file_gm = strat['anatomical_gm_mask'] montage_csf_gm_wm = create_montage_gm_wm_csf('montage_csf_gm_wm_%d' % num_strat, 'montage_csf_gm_wm') workflow.connect(anat_underlay, out_file_anat, montage_csf_gm_wm, 'inputspec.underlay') workflow.connect(csf_overlay, out_file_csf, montage_csf_gm_wm, 'inputspec.overlay_csf') workflow.connect(wm_overlay, out_file_wm, montage_csf_gm_wm, 'inputspec.overlay_wm') workflow.connect(gm_overlay, out_file_gm, montage_csf_gm_wm, 'inputspec.overlay_gm') strat.update_resource_pool({ 'qc___csf_gm_wm_a': (montage_csf_gm_wm, 'outputspec.axial_png'), 'qc___csf_gm_wm_s': (montage_csf_gm_wm, 'outputspec.sagittal_png') }) if not 2 in qc_montage_id_a: qc_montage_id_a[2] = 'csf_gm_wm_a' qc_montage_id_s[2] = 'csf_gm_wm_s' if 'functional_preprocessed' in strat: preproc, out_file_preproc = strat['functional_to_standard'] mean_preproc, out_file_mean_preproc = strat['mean_functional_to_standard'] # make QC Carpet plot carpet_seg = create_qc_carpet('carpet_seg_%d' % num_strat, 'carpet_seg') workflow.connect( preproc, out_file_preproc, carpet_seg, 'inputspec.functional_to_standard' ) workflow.connect( mean_preproc, out_file_mean_preproc, carpet_seg, 'inputspec.mean_functional_to_standard' ) workflow.connect( c.PRIORS_GRAY, 'local_path', carpet_seg, 'inputspec.anatomical_gm_mask' ) workflow.connect( c.PRIORS_WHITE, 'local_path', carpet_seg, 'inputspec.anatomical_wm_mask' ) workflow.connect( c.PRIORS_CSF, 'local_path', carpet_seg, 'inputspec.anatomical_csf_mask' ) strat.update_resource_pool({ 'qc___carpet': (carpet_seg, 'outputspec.carpet_plot'), }) if not 9 in qc_plot_id: qc_plot_id[9] = 'carpet' if 'functional_preprocessed' in strat: # make QC montage for Mean Functional in T1 with T1 edge anat, out_file = strat['anatomical_brain'] m_f_a, out_file_mfa = strat['mean_functional_in_anat'] anat_edge = pe.Node(Function(input_names=['in_file'], output_names=['out_file'], function=afni_Edge3, as_module=True), name='anat_edge_%d' % num_strat) montage_anat = create_montage( 'montage_anat_%d' % num_strat, 'red', 't1_edge_on_mean_func_in_t1') workflow.connect(anat, out_file, anat_edge, 'in_file') workflow.connect(anat_edge, 'out_file', montage_anat, 'inputspec.overlay') workflow.connect(m_f_a, out_file_mfa, montage_anat, 'inputspec.underlay') strat.update_resource_pool({ 'qc___mean_func_with_t1_edge_a': (montage_anat, 'outputspec.axial_png'), 'qc___mean_func_with_t1_edge_s': (montage_anat, 'outputspec.sagittal_png') }) if not 4 in qc_montage_id_a: qc_montage_id_a[4] = 'mean_func_with_t1_edge_a' qc_montage_id_s[4] = 'mean_func_with_t1_edge_s' # make QC montage for Mean Functional in MNI with MNI edge m_f_i, out_file = strat['mean_functional_to_standard'] montage_mfi = create_montage( 'montage_mfi_%d' % num_strat, 'red', 'MNI_edge_on_mean_func_mni') workflow.connect(m_f_i, out_file, montage_mfi, 'inputspec.underlay') montage_mfi.inputs.inputspec.overlay = os.path.abspath( p.resource_filename( 'CPAC', 'resources/templates/MNI152_Edge_AllTissues.nii.gz' ) ) strat.update_resource_pool({'qc___mean_func_with_mni_edge_a': (montage_mfi, 'outputspec.axial_png'), 'qc___mean_func_with_mni_edge_s': (montage_mfi, 'outputspec.sagittal_png')}) if not 5 in qc_montage_id_a: qc_montage_id_a[5] = 'mean_func_with_mni_edge_a' qc_montage_id_s[5] = 'mean_func_with_mni_edge_s' # Link all the derivatives to the QC pages idx = 7 rp = strat.get_resource_pool() for key in sorted(rp.keys()): # qc_outputs is from the outputs CSV if key in qc_outputs: qa_montages(workflow, c, strat, num_strat, qc_montage_id_a, qc_montage_id_s, qc_hist_id, key, idx) idx += 1 return qc_montage_id_a, qc_montage_id_s, qc_hist_id, qc_plot_id