1. Surface_fit_classify [Stage 18]
CIVET
Surface_fit_classify
[Stage 18]

2. Stages nuc_t1_native skull_masking_native stx_register stx_tal_to_7
nuc_inorm_t1
skull_removal
nlfit
mask_classify
pve_curvature
pve
reclassify
segment
cls_volumes
cortical_masking
segment_volumes
surface_classify
artefact
create_wm_hemispheres
segment_mask
expand_from_white_left
expand_from_white_right
slide_left_hemi_obj_back
flip_right_hemi_obj_back
slide_right_hemi_obj_back
calibrate_left_white
calibrate_right_white
laplace_field
gray_surface_left
gray_surface_right
mid_surface_left
mid_surface_right
surface_fit_error
verify_image_nlfit
gyrification_index_left
verify_brain_mask
classify_qc
dataterm_left_surface
brain_mask_qc
gyrification_index_right
dataterm_right_surface
surface_registration_left
surface_registration_right
mean_curvature_20mm_left
mean_curvature_20mm_right
thickness_tlink_20mm_right
thickness_tlink_20mm_left
resample_left_mean_curvature
resample_right_mean_curvature
resample_right_thickness
resample_left_thickness
lobe_area_right
lobe_area_left
verify_clasp
verify_image

3. Stage 18. surface_fit_classify
모듈 : Surface_fit.pm
Label : “fix the classification for surface extraction”
Usage command line
/progs/surface_fit_classify
bin/mincresample
bin/minccalc
bin/skel
bin/mincblur
bin/mincstats
bin/mincdefrag
Input : (1) mni_icbm_00100_classify.mnc (2) mni_icbm_00100_pve_wm.mnc (3) mni_icbm_00100_pve_csf.mnc
Output : (1) final_callosum.mnc (2) final_classify.mnc (3)csf_skel.mnc
의존성 : cortical masking, reclassify

4. [args]
Step 1: Application of the custom mask (ventricules, cerebellum,
sub-cortical gray) and final classification for surface
extraction.
${$pipeline_ref}->addStage(
{ name => "surface_classify",
label => "fix the classification for surface extraction",
inputs => [$cls_correct, $pve_wm, $pve_csf, $nl_transform ],
outputs => [$final_callosum, $final_classify, $skel_csf],
args => ["surface_fit_classify", $cls_correct, $pve_wm, $pve_csf,
$final_callosum, $final_classify, $skel_csf,
$nl_transform, $Second_model_Dir ],
prereqs => $Prereqs } );
[command line]
/usr/local/mni/Dec /CIVET /progs/surface_fit_classify ./classify/mni_icbm_00100_classify.mnc ./classify/mn i_icbm_00100_pve_wm.mnc ./classify/mni_icbm_00100_pve_csf.mnc ./stg_18/final_ca llosum.mnc ./stg_18/final_classify.mnc ./stg_18/csf_skel.mnc ./transforms/nonlinear/ mni_icbm_00100_nlfit_It.xfm /usr/local/mni/Dec /CIVET-1.1.9/models/

5. [surface_fit_classify procedure]
(1) create custom_mask make_custom_mask( $cls_correct, $nl_transform, $custom_mask, $Second_model_Dir ); (2) copy contiguous pieces of white matter from pve image and custom mask fix_wm( $cls_correct, $pve_wm, $custom_mask, $classified_wm_fixed ); (3) fix gray matter voxels fix_gm( $classified_wm_fixed, $classified_wm_gm_fixed ); (4) create a midline mask to separate the hemispheres create_midline_mask( $classified_wm_gm_fixed, $final_callosum ); (5) final classification run( "minccalc", "-clobber", "-expr",      "if(A[1]>0){out=A[1];}else{out=A[0];}",      $classified_wm_gm_fixed, $final_callosum, $final_classify ); (6) create the csf skeleton make_csf_skel( $final_classify, $pve_csf, $skel_csf, $tmpdir );

6. (1) create custom_mask
make_custom_mask( $cls_correct, $nl_transform, $custom_mask, $Second_model_Dir );
##create custom_mask to mask sub-cortical gray and fill up ventricles.##   run( "mincresample", "-clobber", "-like", $cls_correct,        "-invert_transformation", "-nearest_neighbour",        "-transform", $nl_transform, $model_mask, $custom_mask );
mincresample -clobber -like ./classify/mni_icbm_00100_classify.mnc - invert_transformation -nearest_neighbour - transform ./transforms/nonlinear/mni_icbm_00100_nlfit_It.xfm /usr/local/mni/Dec /CIVET /models/Cerebellum_Ventricles_SubCortical_Mask.mnc ./custom_mask.mnc
Usage: mincresample [<options>] <infile> <outfile>  -transformation: File giving world transformation. (Default = identity).  -invert_transformation: Invert the transformation before using it.  -like: Specifies a model file for the resampling.  -nearest_neighbour: Do nearest neighbour interpolation         

7. (1) create custom_mask <model & custom_mask>

8. (1) create custom_mask <custom_mask & classify>

9. (1) create custom_mask <custom_mask (invert)& (non invert)>

10. (2) fix_wm
fix_wm( classified.mnc, pve_wm, custom_mask.mnc, output.mnc )
fix_wm is a little bit of image processing alchemy that attempts // the following:    1) adds the wm skeleton to the wm image by removing any loose ends by blurring and cropping   2) blurs and crops the whole image, and its negative iteratively,    to remove "nonsense" voxels
fix_wm :
(1) Combine custom mask for ventricles and sub-cortical gray into white.
(2) First Pass, add the connected skeleton voxels to the image
(3) now we have pruned the wm pve skeleton, we are going to add it to the classified white matter and then get rid of nonsense voxels
(4) first defrag the gray and add the excluded voxels to csf unless they are surrounded by white
        

11. fix_wm (2)-1:
## Combine custom mask for ventricules and sub-cortical gray into white.##   run( "minccalc", "-byte", "-clobber", "-expr",        "if(abs(A[1]-1)<0.45||abs(A[1]-3)<0.45){out=1;}else{if(abs(A[1]-2)<0.45){out=0;}else{if(A[0]>1.0e- 06){out=1;}else{out=0;}}}", $pve_wm, $custom_mask, $pve_wm_temp );      run( "skel", $pve_wm_temp, $pve_wm_skel );   run( "minccalc", "-clobber", "-expr",        "if(abs(A[1]-1)<0.45||abs(A[1]-3)<0.45){out=3;}else{if(abs(A[1]-2)<0.45){out=1;}else{out=A[0];}}",        $classified, $custom_mask, $classified_temp) ; [1] minccalc -byte -clobber -expr 'if(abs(A[1]-1)<0.45||abs(A[1]- 3)<0.45){out=1;}else{if(abs(A[1]-2)<0.45){out=0;}else{if(A[0]>1.0e- 06){out=1;}else{out=0;}}}' ../classify/mni_icbm_00100_pve_wm.mnc ./custom_mask.m nc ./pve_plugged.mnc
[Usage]: minccalc [options] [<in1.mnc> ...] <out.mnc>
[options]
-byte: Write out byte data.
-expression: Expression to use in calculations.
-clobber: Overwrite existing file.         

12. fix_wm (2)-1-1 <pve_wm & pve_plugged>

13. fix_wm (2)-1-1 <custom_mask & pve_plugged>

14. fix_wm (2)-1-2: “ skel ” : Skeletonizes a binary thresholded minc volume
[2] skel ./pve_plugged.mnc ./temp_skel.mnc
[Usage] : skel <input.mnc> <output.mnc>

15. fix_wm (2)-1-3:
run( "minccalc", "-clobber", "-expr", "if(abs(A[1]-1)<0.45||abs(A[1]-3)<0.45){out=3;}
else{if(abs(A[1]-2)<0.45){out=1;}else{out=A[0];}}", $classified, $custom_mask, $classified_temp) ;
minccalc -clobber -expr 'if(abs(A[1]-1)<0.45||abs(A[1]-3)<0.45){out=3;}else{if(abs(A[1]- 2)<0.45){out=1;}else{out=A[0];}}' ../classify/mni_icbm_00100_classify.mnc ./custom_mask.mnc ./cl assified_plugged.mnc

16. fix_wm (2)-1-3: [custom_mask & classified_plugged]

17. fix_wm (2)-2:
### First Pass, add the connected skeleton voxels to the image ##    run( "mincblur", "-clobber", "-fwhm", "2", $pve_wm_skel, $temp_blur );       run( "minccalc", "-clobber", "-expr", "out=(A[0]>${integrity}||A[2]==3)&&A[1];", $temp_blur, $pve_wm_skel, $classified_temp, $pve_wm_skel_new );       run( "minccalc", "-clobber", "-expr", "out=abs(A[0]-A[1]);",          $pve_wm_skel, $pve_wm_skel_new, $temp_diff);     "mincstats", "-sum", $temp_diff        
run( "mv", "-f", $pve_wm_skel_new, $pve_wm_skel );   [1] mincblur -clobber -fwhm 2 ./temp_skel.mnc ./temp_blur.mnc
Usage: mincblur [<options>] <inputfile> <output_basename>
[options]
-fwhm: Full-width-half-maximum of gaussian kernel         [2] minccalc -clobber -expr 'out=(A[0]>0.3||A[2]==3)&&A[1];' ./temp_blur.mnc ./temp_skel.mnc ./classified_plug ged.mnc ./temp_skel_new.mnc

18. fix_wm (2)-2-1: [temp_skel.mnc & temp_blur.mnc]

19. fix_wm (2)-2-2: [classified_plugged & temp_skel_new ]

20. [3] minccalc -clobber -expr 'out=abs(A[0]-A[1]);' ./temp_skel.mnc
./temp_skel_new.mnc ./temp_diff.mnc
[4] mincstats -sum ./temp_diff.mnc
## Mincstats will calculate simple statistical measures across all voxels of a minc file. ##
Usage: mincstats [options] <infile.mnc>
[options] : -sum : SUM >> Statistics (Printed in this order)
** [4] “mincstats” result **
Iteration:0 Voxels changed:5775 -> temp_diff.mnc의 모든 voxel sum
Iteration:1 Voxels changed:812
Iteration:2 Voxels changed:239
Iteration:3 Voxels changed:75
Iteration:4 Voxels changed:42
Iteration:5 Voxels changed:15
Iteration:6 Voxels changed:9
Iteration:7 Voxels changed:6
Iteration:8 Voxels changed:1
Iteration:9 Voxels changed:0

21. fix_wm (2)-2-3: [temp_skel_new.mnc & temp_diff.mnc]

22. fix_wm (2)-3:
# now we have pruned the wm pve skeleton, we are going to add it to the classified white matter and then get rid of nonsense voxels. ##
  run( "minccalc", "-clobber", "-expr", "out=A[0]||(abs(A[1]-3)<0.45);",        $pve_wm_skel, $classified_temp, $wm_with_skel) ;   run( "mincblur", "-clobber", "-fwhm", "2", $wm_with_skel, $temp_blur );     run( "minccalc", "-clobber", "-expr", "out=if(A[0]<${integrity}&&A[1]>0.5){out==0;}
else{if(A[0]>(1-${integrity})&&A[1]<0.5){out==1;}else{out=A[1];}};", $temp_blur, $wm_with_skel, $wm_with_skel_new );     run( "minccalc", "-clobber", "-expr", "out=abs(A[0]-A[1]);", $wm_with_skel, $wm_with_skel_new, $temp_diff );  "mincstats", "-sum", $temp_diff    
  run( "mv", "-f", $wm_with_skel_new, $wm_with_skel ); [1] minccalc -clobber -expr 'out=A[0]||(abs(A[1]- 3)<0.45);' ./temp_skel_final.mnc ./classified_plugged.mnc ./wm_with_skel.mnc       

23. fix_wm (2)-3-1: [classified_plugged & wm_with_skel.mnc]

24. fix_wm (2)-3-1: [temp_skel_final.mnc & wm_with_skel.mnc]

25. [2] mincblur -clobber -fwhm 2 ./wm_with_skel.mnc ./temp_blur_wm.mnc

26. [3] minccalc -clobber -expr 'out=if(A[0]<0. 3&&A[1]>0
[3] minccalc -clobber -expr 'out=if(A[0]<0.3&&A[1]>0.5){out==0;}else{if(A[0]>(1- 0.3)&&A[1]<0.5){out==1;}else{out=A[1];}};' ./temp_blur_wm.mnc ./wm_with_skel.mnc ./wm_with_skel_new.mnc

27. [4] minccalc -clobber -expr 'out=abs(A[0]-A[1]);'. /wm_with_skel. mnc
[4] minccalc -clobber -expr 'out=abs(A[0]-A[1]);' ./wm_with_skel.mnc ./wm_with_skel_new.mnc ./temp_diff_wm.mnc

28. [5] mincstats -sum. /temp_diff_wm. mnc. [5] “mincstats” result
[5] mincstats -sum ./temp_diff_wm.mnc ** [5] “mincstats” result ** Iteration B:0 Voxels changed:1540 ->> temp_diff_wm.mnc의 모든 voxel수 Iteration B:1 Voxels changed:345 Iteration B:2 Voxels changed:132 Iteration B:3 Voxels changed:66 Iteration B:4 Voxels changed:43 Iteration B:5 Voxels changed:21 Iteration B:6 Voxels changed:17 Iteration B:7 Voxels changed:6 Iteration B:8 Voxels changed:2 Iteration B:9 Voxels changed:1 Iteration B:10 Voxels changed:0

29. [fix_wm-(2)-3 final]

30. fix_wm (2)-4:
# first defrag the gray and add the excluded voxels to csf unless they are surrounded by white   run( "mincdefrag", $wm_with_skel, $wm_with_skel_new, "1", "27", "100000");   run( "minccalc", "-clobber", "-expr", "out=A[0]<0.5;",        $wm_with_skel_new, $wm_with_skel );   run( "mincdefrag", $wm_with_skel, $wm_with_skel_new, "1", "27", "100000");   run( "minccalc", "-clobber", "-expr", "out=A[0]<0.5;",        $wm_with_skel_new, $wm_with_skel );   run( "minccalc", "-clobber", "-expr", "if(abs(A[0]-1)>0.45&&abs(A[1]-3)<0.45){out=2;}
else{if(abs(A[0]-1)<0.45&&abs(A[1]-3)>0.45){out=3}else{out=A[1];}};",        $wm_with_skel, $classified_temp , $output ); [1] mincdefrag ./wm_with_skel_10.mnc ./wm_with_skel_defrag.mnc [Usage]: mincdefrag input.mnc output.mnc label stencil [max_connect]
label = integer label for voxel intensity
stencil = number of neighbours (6, 19, 27)
max_connect = threshold for number of connected voxels
>> ** “[1]mincdefrag” result **
Kept total of voxels of label 1
Removed total of 1670 voxels of label 1

31. fix_wm (2)-4-1: [wm_with_skel_10.mnc & wm_with_skel_defrag.mnc ]

32. [2] minccalc -clobber -expr 'out=A[0]<0. 5;'. /wm_with_skel_defrag
[2] minccalc -clobber -expr 'out=A[0]<0.5;' ./wm_with_skel_defrag.mnc ./wm_with_skel_defrag_modify.mnc

33. [3] mincdefrag ./wm_with_skel_defrag_modify.mnc
./wm_with_skel_defrag_modify_defrag.mnc
**result** : Kept total of voxels of label 1, Removed total of 449 voxels of label 1

34. [4] minccalc -clobber -expr 'out=A[0]<0. 5;'
[4] minccalc -clobber -expr 'out=A[0]<0.5;' ./wm_with_skel_defrag_modify_defrag.mnc
./wm_with_skel_defrag_modify_defrag_modify.mnc

35. [5] minccalc -clobber -expr 'if(abs(A[0]-1)>0. 45&&abs(A[1]-3)<0
[5] minccalc -clobber -expr 'if(abs(A[0]-1)>0.45&&abs(A[1]-3)<0.45){out=2;}else{if(abs(A[0]- 1)<0.45&&abs(A[1]-3)>0.45){out=3}else{out=A[1];}};'
./wm_with_skel_defrag_modify_defrag_modify.mnc ./classified_plugged.mnc ./classified_wm_fixed.mnc

36. [5] wm_with_skel_defrag_modify_defrag_modify.mnc & classified_wm_fixed.mnc

37. (3) fix_gm
fix_gm is “ fix gray matter voxels” >> fix_gm( $classified_wm_fixed, $classified_wm_gm_fixed ); fix_gm is a little bit of image processing alchemy that attempts the following:    1) adds the wm skeleton to the wm image by removing any loose ends       by blurring and cropping   2) blurs and crops the whole image, and its negative iteratively,      to remove "nonsense" voxels # fix_gm( classified.mnc, output.mnc )
fix_gm (3) -1:
run( "minccalc", "-clobber", "-expr", 'out=abs(A[0]-3)<0.45;', $classified, $temp_white ); run( "mincblur", "-clobber", "-fwhm", "2", $temp_white, $temp_white_blur_prefix ); run( "minccalc", "-clobber", "-expr", 'out=abs(A[0]-2)<0.45;', $classified, $temp_gray ); fix_gm (3) -1-[1]:
[1] minccalc -clobber -expr 'out=abs(A[0]-3)<0.45;'
./classified_wm_fixed.mnc ./temp_white.mnc
       

38. fix_gm (3)-1-[1] [classified_wm_fixed.mnc & temp_white.mnc]

39. fix_gm (3)-1-[2] : mincblur -clobber -fwhm 2. /temp_white. mnc
fix_gm (3)-1-[2] : mincblur -clobber -fwhm 2 ./temp_white.mnc ./temp_white

40. fix_gm (3)-1-[3] : minccalc -clobber -expr 'out=abs(A[0]-2)<0. 45;'
fix_gm (3)-1-[3] : minccalc -clobber -expr 'out=abs(A[0]-2)<0.45;' ./classified_wm_fixed.mnc ./temp_gray.mnc

41. fix_gm (3)-2: “mincdefrag” is ##first defrag the gray ## mincdefrag
fix_gm (3)-2: “mincdefrag” is ##first defrag the gray ## mincdefrag ./temp_gray.mnc ./temp_gray_defrag.mnc **result ** : Kept total of voxels of label 1, Removed total of 917 voxels of label 1

42. fix_gm (3)-3
###then go through iterations of blur and remove until converged   while (!$done && $count<50){     run( "mincblur", "-clobber", "-fwhm", "2", $temp_gray_defrag, $temp_gray_blur_prefix );       run( "minccalc", "-clobber", "-expr",          'out=(A[0]>0.45&&abs(A[1]-1)<0.45)||(A[0]>0.001&&A[2]>0.01&&abs(A[1]-1)<0.45);',          $temp_gray_blur, $temp_gray_defrag, $temp_white_blur, $temp_gray_new);       run( "minccalc", "-clobber", "-expr", 'out=abs(A[0]-A[1]);',          $temp_gray_defrag, $temp_gray_new, $temp_gray_diff ); = ("mincstats", "-sum", $temp_gray_diff) ;     print ;     my $stats_result = ;     = split/\s+/, $stats_result ;     print ("Iteration:${count}\tVoxels changed:${line[1]}\n") ;     if ($line[1]<20) { $done = 1 ; }     $count = $count+1 ;     run("mv", "-f", $temp_gray_new, $temp_gray_defrag) ;   }        
fix_gm (3)-3 –[1]
mincblur -clobber -fwhm 2 ./temp_gray_defrag.mnc ./temp_gray_defrag_1

43. fix_gm (3)-3-[1] : [temp_gray_defrag. mnc & temp_gray_defrag_1_blur
fix_gm (3)-3-[1] : [temp_gray_defrag.mnc & temp_gray_defrag_1_blur.mnc]

44. fix_gm (3)-3-[2] : minccalc -clobber -expr 'out=(A[0]>0
fix_gm (3)-3-[2] : minccalc -clobber -expr 'out=(A[0]>0.45&&abs(A[1]- 1)<0.45)||(A[0]>0.001&&A[2]>0.01&&abs(A[1]-1)<0.45);'
./temp_gray_defrag_1_blur.mnc ./temp_gray_defrag.mnc ./temp_white_blur.mnc ./temp_gray_defrag_new.mnc

45. fix_gm (3)-3-[3] : minccalc -clobber -expr 'out=abs(A[0]-A[1]);'
./temp_gray_defrag.mnc ./temp_gray_defrag_new.mnc ./temp_gray_diff.mnc

46. fix_gm (3)-3-[3] : minccalc -clobber -expr 'out=abs(A[0]-A[1]);'
./temp_gray_defrag.mnc ./temp_gray_defrag_new.mnc ./temp_gray_diff.mnc
** “mincstats” result **
Iteration:0 Voxels changed:5050
Iteration:1 Voxels changed:2214
Iteration:2 Voxels changed:1461
Iteration:3 Voxels changed:1123
Iteration:4 Voxels changed:877
Iteration:5 Voxels changed:677
Iteration:6 Voxels changed:525 .
Iteration:49 Voxels changed:16

47. fix_gm (3)-3-final : [temp_gray_defrag_50.mnc & temp_gray_defrag.mnc]

48. fix_gm (3)-3-final] : [temp_gray_diff.mnc & temp_gray_diff_49.mnc]

49. fix_gm (3)-3-final : [temp_gray_defrag_50. mnc & sub
fix_gm (3)-3-final : [temp_gray_defrag_50.mnc & sub.mnc(final-initial)]

50. ** “mincdefrag” result **
fix_gm_3_4 [1] run( "mincdefrag", $temp_gray_defrag, $temp_gray_new, "1", "27", "100000" ); mincdefrag ./temp_gray_defrag_50.mnc ./temp_gray_defrag_new.mnc
** “mincdefrag” result **
Kept total of voxels of label 1, Removed total of 0 voxels of label 1

51. fix_gm_3_4 [2] [temp_gray_defrag_new. mnc & classified_wm_gm_fixed
fix_gm_3_4 [2] [temp_gray_defrag_new.mnc & classified_wm_gm_fixed.mnc] run( "minccalc", "-clobber", "-expr", 'if(A[0]<0.5&&A[1]>0.5&&A[2]>0.25){out=2}else{if(A[0]<0.5&&A[1]>0.5&&A[2]<0.25){out=1}else{out=A [3];}}', $temp_gray_new, $temp_gray, $temp_white_blur, $classified, $result );

52. fix_gm_3_4 [2] : [classified_wm_fixed. mnc & classified_wm_gm_fixed
fix_gm_3_4 [2] : [classified_wm_fixed.mnc & classified_wm_gm_fixed.mnc]

53. # create_midline_mask extracts . >> create_midline_mask classified.mnc output.mnc # The creation of the midline mask below will work with any template (0.5mm, 1.0mm, for example), assuming that the centerline voxel is at x=0.   run( "minccalc", "-clobber", "-byte", "-expr", "out=1;", $classify, $filled );   run( "mincresample", "-clobber", "-xstart", 0, "-xnelements", 1, $filled, $mid_tmp );   run( "mincresample", "-clobber", "-like", $classify, $mid_tmp, $midline_mask );   run( "minccalc", "-clobber", "-expr", "out=abs(A[0]-3)<0.45&&A[1];",        $classify, $midline_mask, $callosum_with_bits );   run( "mincdefrag", $callosum_with_bits, $callosal_defrag, 1, 27, 1000 );   run( "mincblur", "-clobber", "-fwhm", 2, $callosal_defrag, $callosal_blur );                   run( "minccalc", "-clobber", "-byte", "-expr",        "if(A[0]>0.0001&&A[1]==1){out=1}else{if(A[0]>0.08){out=2}else{out=0;}};",        $callosal_blur, $midline_mask, $output );
fix_gm_4 [1] : minccalc -clobber -byte -expr 'out=1;' ./classified_wm_gm_fixed.mnc ./filled.mnc
fix_gm_4 [2] : mincresample -clobber -xstart 0 -xnelements 1 ./filled.mnc ./mid_tmp.mnc
fix_gm_4 [3] : mincresample -clobber -like ./classified_wm_gm_fixed.mnc ./mid_tmp.mnc
./midline_mask.mnc
fix_gm_4 [4] : minccalc -clobber -expr 'out=abs(A[0]-3)<0.45&&A[1];'
./classified_wm_gm_fixed.mnc ./midline_mask.mnc ./callosum_with_bits.mnc
fix_gm_4 [5] : mincdefrag ./callosum_with_bits.mnc ./callosum_defrag.mnc
fix_gm_4 [6] : mincblur -clobber -fwhm 2 ./callosum_defrag.mnc ./callosal_blur.mnc
fix_gm_4 [7] : minccalc -clobber -byte -expr 'if(A[0]>0.0001&&A[1]==1){out=1}else{if(A[0]>0.08){out=2}else{out=0;}};'
./callosal_blur.mnc_blur.mnc ./midline_mask.mnc ./final_callosum.mnc

54. mincresample
“mincresample” will resample a minc file along new spatial dimensions with new voxel positions
Usage: mincresample [<options>] <infile> <outfile>
-xstart: Start point along the X dimension
-start: Start point along each dimension (X, Y, Z)
Default value: e e e+308
-xnelements: Number of elements along the X dimension
mincresample -clobber -xstart 0 -xnelements 1 ./filled.mnc ./mid_tmp.mnc

55. fix_gm_4 [1] : minccalc -clobber -byte -expr 'out=1;'
fix_gm_4 [1] : minccalc -clobber -byte -expr 'out=1;' ./classified_wm_gm_fixed.mnc ./filled.mnc

56. fix_gm_4 [2] : mincresample -clobber -xstart 0 -xnelements 1. /filled
fix_gm_4 [2] : mincresample -clobber -xstart 0 -xnelements 1 ./filled.mnc ./mid_tmp.mnc fix_gm_4 [3] : mincresample -clobber -like ./classified_wm_gm_fixed.mnc ./mid_tmp.mnc ./midline_mask.mnc

57. fix_gm_4 [4] : minccalc -clobber -expr 'out=abs(A[0]-3)<0
fix_gm_4 [4] : minccalc -clobber -expr 'out=abs(A[0]-3)<0.45&&A[1];' ./classified_wm_gm_fixed.mnc ./midline_mask.mnc ./callosum_with_bits.mnc

58. fix_gm_4 [5] : mincdefrag. /callosum_with_bits. mnc. /callosum_defrag
fix_gm_4 [5] : mincdefrag ./callosum_with_bits.mnc ./callosum_defrag.mnc
**result ** : Kept total of 1796 voxels of label 1, Removed total of 0 voxels of label 1

59. fix_gm_4 [6] : mincblur -clobber -fwhm 2. /callosum_defrag. mnc
fix_gm_4 [6] : mincblur -clobber -fwhm 2 ./callosum_defrag.mnc ./callosal_blur.mnc

60. fix_gm_4 [7] : minccalc -clobber -byte -expr 'if(A[0]>0
fix_gm_4 [7] : minccalc -clobber -byte -expr 'if(A[0]>0.0001&&A[1]==1){out=1}else{if(A[0]>0.08) {out=2}else{out=0;}};' ./callosal_blur.mnc_blur.mnc ./midline_mask.mnc ./final_callosum.mnc

61. # final classification run( "minccalc", "-clobber", "-expr", "if(A[1]>0){out=A[1];}else{out=A[0];}",      $classified_wm_gm_fixed, $final_callosum, $final_classify );

62. # final classification run( "minccalc", "-clobber", "-expr", "if(A[1]>0){out=A[1];}else{out=A[0];}",      $classified_wm_gm_fixed, $final_callosum, $final_classify );

63. # create the csf skeleton   # Make sure there is a layer of CSF around the cortex:      - select white + gray      - dilate white + gray by one voxel layer      - add csf to the skeleton in the dilated layer of the mask      - create the fixed skeleton to be used in the Laplacian field for the gray surface extraction.   # NOTE: If you don't do this step, the skeleton will go through the gray matter if there is no layer of csf between gray and background. This will truncate the gray matter and make the cortex thinner.   run( "minccalc", "-clobber", "-byte", "-expression",        "if(A[0]>1.5){out=1;}else{out=0;}", $cls_correct, $wm_gm_mask );   run( "dilate_volume", $wm_gm_mask, $wm_gm_maskD, "1", "26", "1" );   run( "minccalc", "-clobber", "-byte", "-expression",        "if((A[1]<1.5&&A[2]>0.5)||A[0]>1.0e-06){out=1;}else{out=0;}",        $pve_csf, $cls_correct, $wm_gm_maskD, $pve_csf_dil );   run( "skel", $pve_csf_dil, $skel_csf );
[1] minccalc -clobber -byte -expression 'if(A[0]>1.5){out=1;}else{out=0;}'
final_classify.mnc ./wm_gm_mask.mnc
[2] dilate_volume ./wm_gm_mask.mnc ./wm_gm_mask_dil.mnc >> “result” :
[3] minccalc -clobber -byte -expression 'if((A[1]<1.5&&A[2]>0.5)||A[0]>1.0e- 06){out=1;}else{out=0;}' ../../classify/mni_icbm_00100_pve_csf.mnc final_classify.mnc ./wm_gm_mask_dil.mnc ./pve_csf_dil.mnc
[4] skel ./pve_csf_dil.mnc csf_skel.mnc

64. dilate_volume
Usage: dilate_volume input.mnc output.mnc dilation_value [6|26] [n_dilations] [mask.mnc min_mask max_mask]
Note: Dilates all regions of value dilation_value, by n_dilations of 3X3X3, (1 dilation by default). You can specify 6 or 26 neighbours, default being 26. If the mask volume and range is specified, then only voxels in the specified mask range will be dilated.

65. [1] minccalc [final_classify.mnc & wm_gm_mask.mnc]

66. [2] dilate_volume [wm_gm_mask.mnc & wm_gm_mask_dil.mnc ]

67. [3] minccalc [wm_gm_mask_dil.mnc & pve_csf_dil.mnc]

68. [4] skel [pve_csf_dil.mnc & csf_skel.mnc]