Action and rest tremor map to distinct networks within the primary motor cortex.

1. function varargout=ea_normalize_spmshoot(options)
2. % This is a function that normalizes both a copy of transversal and coronal
3. % images into MNI-space. The goal was to make the procedure both robust and
4. % automatic, but still, it must be said that normalization results should
5. % be taken with much care because all reconstruction results heavily depend
6. % on these results. Normalization of DBS-MR-images is especially
7. % problematic since usually, the field of view doesn't cover the whole
8. % brain (to reduce SAR-levels during acquisition) and since electrode
9. % artifacts can impair the normalization process. Therefore, normalization
10. % might be best archieved with other tools that have specialized on
11. % normalization of such image data.
12. %
13. % The procedure used here uses the SPM DARTEL approach to map a patient's
14. % brain to MNI space directly. Unlike the usual DARTEL-approach, which is
15. % usually used for group studies, here, DARTEL is used for a pairwise
16. % co-registration between patient anatomy and MNI template. It has been
17. % shown that DARTEL also performs superior to many other normalization approaches
18. % also in a pair-wise setting e.g. in
19. % Klein, A., et al. (2009). Evaluation of 14 nonlinear deformation algorithms
20. % applied to human brain MRI registration. NeuroImage, 46(3), 786?802.
21. % doi:10.1016/j.neuroimage.2008.12.037
22. %
23. % Since a high resolution is needed for accurate DBS localizations, this
24. % function applies DARTEL to an output resolution of 0.5 mm isotropic. This
25. % makes the procedure quite slow.
27. % The function uses some code snippets written by Ged Ridgway.
28. % __________________________________________________________________________________
29. % Copyright (C) 2014 Charite University Medicine Berlin, Movement Disorders Unit
30. % Andreas Horn
33. if ischar(options) % return name of method.
34. varargout{1}='SPM12 SHOOT (Ashburner 2011)';
35. varargout{2}=1; % dummy output
36. varargout{3}=0; % hassettings.
37. varargout{4}=1; % is multispectral
38. return
39. end
41. disp('Segmenting preoperative version (Import to DARTEL-space)');
42. preopImages = struct2cell(options.subj.coreg.anat.preop);
43. ea_newseg(preopImages, 1, 1);
44. disp('Segmentation of preoperative MRI done.');
46. [directory, preopAnchorName] = fileparts(preopImages{1});
47. directory = [directory, filesep];
49. % Check if SHOOT template is available
50. if exist([ea_space(options,'dartel'),'shootmni_6.nii'],'file')
51. % There is a DARTEL-Template. Check if it will match:
52. Vt=spm_vol([ea_space(options,'dartel'),'shootmni_6.nii']);
53. Vp=spm_vol([directory, 'rc1', preopAnchorName, '.nii']);
54. if ~isequal(Vp.dim,Vt(1).dim) || ~isequal(Vp.mat,Vt(1).mat) % Dartel template not matching. -> create matching one.
55. ea_create_tpm_darteltemplate;
56. end
57. else % no dartel template present. -> Create matching dartel templates from highres version.
58. keyboard
59. ea_create_tpm_darteltemplate;
60. end
62. % Forward
63. matlabbatch{1}.spm.tools.shoot.warp1.images = {
64. {[directory,'rc1',preopAnchorName,'.nii,1']}
65. {[directory,'rc2',preopAnchorName,'.nii,1']}
66. {[directory,'rc3',preopAnchorName,'.nii,1']}}';
67. matlabbatch{1}.spm.tools.shoot.warp1.templates = {[ea_space(options,'dartel'),'shootmni_1.nii']
68. [ea_space(options,'dartel'),'shootmni_2.nii']
69. [ea_space(options,'dartel'),'shootmni_3.nii']
70. [ea_space(options,'dartel'),'shootmni_4.nii']
71. [ea_space(options,'dartel'),'shootmni_5.nii']
72. [ea_space(options,'dartel'),'shootmni_6.nii']};
74. spm_jobman('run',{matlabbatch});
75. disp('*** Shoot coregistration of preoperative version worked.');
76. clear matlabbatch;
78. movefile([directory,'y_rc1', preopAnchorName, '_Template.nii'], [directory,'y_ea_normparams.nii']);
80. % Inverse
81. matlabbatch{1}.spm.util.defs.comp{1}.inv.comp{1}.def = {[directory,'y_ea_normparams.nii']};
82. matlabbatch{1}.spm.util.defs.comp{1}.inv.space = {[directory, preopAnchorName, '.nii']};
83. matlabbatch{1}.spm.util.defs.out{1}.savedef.ofname = 'ea_inv_normparams.nii';
84. matlabbatch{1}.spm.util.defs.out{1}.savedef.savedir.saveusr = {directory};
85. spm_jobman('run',{matlabbatch});
86. disp('*** Exported normalization parameters to y_ea_inv_normparams.nii');
87. clear matlabbatch;
89. % Delete rc* files and u_rc1* file
90. ea_delete([directory, 'rc*', preopAnchorName, '.nii']);
91. ea_delete([directory, '*_rc1', preopAnchorName, '_Template.nii']);
93. % Rename Segmentations (c1, c2, c3)
94. mod = replace(options.subj.AnchorModality, textBoundary('start') + alphanumericsPattern + "_", "");
95. movefile([directory, 'c1', preopAnchorName, '.nii'], setBIDSEntity(preopImages{1}, 'mod', mod, 'label', 'GM', 'suffix', 'mask'));
96. movefile([directory, 'c2', preopAnchorName, '.nii'], setBIDSEntity(preopImages{1}, 'mod', mod, 'label', 'WM', 'suffix', 'mask'));
97. movefile([directory, 'c3', preopAnchorName, '.nii'], setBIDSEntity(preopImages{1}, 'mod', mod, 'label', 'CSF', 'suffix', 'mask'));
99. % Deformation fields to itk
100. ea_mkdir(fileparts(options.subj.norm.transform.forwardBaseName));
101. ea_spm_fwd_displacement_field_to_ants([directory, 'y_ea_normparams.nii'], [options.subj.norm.transform.forwardBaseName, 'ants.nii.gz']);
102. ea_slicer_invert_transform([options.subj.norm.transform.forwardBaseName, 'ants.nii.gz'], options.subj.coreg.anat.preop.(options.subj.AnchorModality), [options.subj.norm.transform.inverseBaseName, 'ants.nii.gz']);
103. delete([directory, 'y_ea_normparams.nii'])
104. delete([directory, 'y_ea_inv_normparams.nii'])
106. ea_apply_normalization(options)
108. % add methods dump:
109. [scit, lcit] = ea_getspacedefcit;
110. cits={
111. 'Ashburner, J., & Friston, K. J. (2005). Unified segmentation., 26(3), 839?851. http://doi.org/10.1016/j.neuroimage.2005.02.018'
112. 'Ashburner, J., & Friston, K. J. (2011). Diffeomorphic registration using geodesic shooting and Gauss?Newton optimisation. NeuroImage, 55(3), 954?967. http://doi.org/10.1016/j.neuroimage.2010.12.049'
113. 'Horn, A., & Kuehn, A. A. (2015). Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations. NeuroImage, 107, 127?135. http://doi.org/10.1016/j.neuroimage.2014.12.002'};
115. if ~isempty(lcit)
116. cits = [cits; {lcit}];
117. end
119. modality = regexp(preopImages, '(?<=_)[^\W_]+(?=\.nii(\.gz)?$)', 'match', 'once');
121. ea_methods(options,['Pre- (and post-) operative acquisitions were spatially normalized into ',ea_getspace,' space ',scit,' based on preoperative acquisition(s) (',strjoin(modality, ', '),') using a'...
122. ' diffeomorphic registration algorithm using geodesic shooting and Gauss-Neuwton optimisation (SHOOT) as implemented in SPM12 (Ashburner 2011; www.fil.ion.ucl.ac.uk/spm/software/).',...
123. ' SHOOT registration was performed by directly registering tissue segmentations of preoperative acquisitions (obtained using the unified Segmentation approach as implemented in SPM12 (Ashburner 2005)',...
124. ' to a SHOOT template created from tissue priors defined by the MNI (ICBM 152 Nonlinear asymmetric 2009b atlas; http://nist.mni.mcgill.ca/?p=904)',...
125. ' supplied within Lead-DBS software (Horn 2015; www.lead-dbs.org).'],cits);

ea_normalize_spmshoot.m at commit 5b1008d, under GPL-3.0 · at the source