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Dear AFNI users-
We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:
Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.
The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.
Sincerely, AFNI HQ
We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:
https://discuss.afni.nimh.nih.gov
Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.
The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.
Sincerely, AFNI HQ
| November 29, 2017 11:14PM | |
Registered: 6 years ago Posts: 1 |
Hi,
I am doing registration between two datasets, that is, the DTI dataset and a parcellated dataset.
Here are the scripts I used here (dti_fa_color.nii.gz is the DTI dataset, and aparc.a2009s+aseg_REN_all.nii is the parcellated dataset) :
3dcalc -a dti_fa_color.nii.gz -expr 'a' -prefix dti_fa_color
align_epi_anat.py -anat aparc.a2009s+aseg_REN_all.nii.gz -epi dti_fa_color+orig -epi_base 0 -anat_has_skull no -epi_strip 3dAutomask -volreg off -tshift off -big_move
However, after running the scripts, I got the following 5 warnings. The main problem lies in that:
If you are performing spatial transformations on an oblique dset,
such as .......,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
I have seen some similar questions in this forum, but I have not solved my problem. Although these are some warnings instead of errors, the registration result is bad. Could you please give me some suggestions. Many thanks!
The version of AFNI I used is --- binary linux_ubuntu_16_64: Jun 6 2017 (Version AFNI_17.1.09)
Here are the results I got:
align_epi_anat.py -anat aparc.a2009s+aseg_REN_all.nii.gz -epi dti_fa_co
lor+orig -epi_base 0 -anat_has_skull no -epi_strip 3dAutomask -volreg off -tshift off -giant_move
#++ align_epi_anat version: 1.57
#++ turning off volume registration
#Script is running (command trimmed):
3dAttribute DELTA ./dti_fa_color+orig
#Script is running (command trimmed):
3dAttribute DELTA ./dti_fa_color+orig
#Script is running (command trimmed):
3dAttribute DELTA ./aparc.a2009s+aseg_REN_all.nii.gz
#++ Multi-cost is lpc
#++ Removing all the temporary files
#Script is running:
\rm -f ./__tt_dti_fa_color*
#Script is running:
\rm -f ./__tt_aparc.a2009s+aseg_REN_all*
#Script is running (command trimmed):
3dcopy ./aparc.a2009s+aseg_REN_all.nii.gz ./__tt_aparc.a2009s+aseg_REN_all+orig
++ 3dcopy: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
#Script is running (command trimmed):
3dinfo ./__tt_aparc.a2009s+aseg_REN_all+orig | \grep 'Data Axes Tilt:'|\grep 'Oblique'
#++ Dataset /media/raymondlab/DATA/Yuqi/freesurfer_subjects/pure_T1/0cyf/SUMA/__tt_aparc.a2009s+aseg_REN_all+orig is not oblique
#Script is running (command trimmed):
3dinfo ./dti_fa_color+orig | \grep 'Data Axes Tilt:'|\grep 'Oblique'
#++ Dataset /media/raymondlab/DATA/Yuqi/freesurfer_subjects/pure_T1/0cyf/SUMA/dti_fa_color+orig is ***oblique****
#Script is running (command trimmed):
3dAttribute DELTA ./__tt_aparc.a2009s+aseg_REN_all+orig
#++ Spacing for anat to oblique epi alignment is 1.000000
#++ Matching obliquity of anat to epi
#Script is running (command trimmed):
3dWarp -verb -card2oblique ./dti_fa_color+orig -prefix ./__tt_aparc.a2009s+aseg_REN_all_ob -newgrid 1.000000 ./__tt_aparc.a2009s+aseg_REN_all+orig | \grep -A 4 '# mat44 Obliquity Transformation ::' > ./__tt_aparc.a2009s+aseg_REN_all_obla2e_mat.1D
++ 3dWarp: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: RW Cox
#++ using 0th sub-brick because only one found
#Script is running (command trimmed):
3dbucket -prefix ./__tt_dti_fa_color_ts ./dti_fa_color+orig'[0]'
++ 3dbucket: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
#++ removing skull or area outside brain
#Script is running (command trimmed):
3dAutomask -apply_prefix ./__tt_dti_fa_color_ts_ns ./__tt_dti_fa_color_ts+orig
++ 3dAutomask: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: Emperor Zhark
*+ WARNING: If you are performing spatial transformations on an oblique dset,
such as ./__tt_dti_fa_color_ts+orig.BRIK,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
See 3dWarp -help for details.
++ Oblique dataset:./__tt_dti_fa_color_ts+orig.BRIK is 5.964928 degrees from plumb.
++ Loading dataset ./__tt_dti_fa_color_ts+orig
++ Forming automask
+ Fixed clip level = 14.898818
+ Used gradual clip level = 13.122265 .. 17.882113
+ Number voxels above clip level = 106456
+ Clustering voxels ...
+ Largest cluster has 104109 voxels
+ Clustering voxels ...
+ Largest cluster has 78274 voxels
+ Filled 4709 voxels in small holes; now have 82983 voxels
+ Filled 147 voxels in large holes; now have 83130 voxels
+ Clustering voxels ...
+ Largest cluster has 82934 voxels
+ Clustering non-brain voxels ...
+ Clustering voxels ...
+ Largest cluster has 380281 voxels
+ Mask now has 83039 voxels
++ 83039 voxels in the mask [out of 463320: 17.92%]
++ first 4 x-planes are zero [from R]
++ last 4 x-planes are zero [from L]
++ first 3 y-planes are zero [from P]
++ last 7 y-planes are zero [from A]
++ first 3 z-planes are zero [from I]
++ last 5 z-planes are zero [from S]
++ applying mask to original data
++ Writing masked data
++ CPU time = 0.000000 sec
#++ Computing weight mask
#Script is running (command trimmed):
3dBrickStat -automask -percentile 90.000000 1 90.000000 ./__tt_dti_fa_color_ts_ns+orig
#++ Applying threshold of 71.627998 on /media/raymondlab/DATA/Yuqi/freesurfer_subjects/pure_T1/0cyf/SUMA/__tt_dti_fa_color_ts_ns+orig
#Script is running (command trimmed):
3dcalc -datum float -prefix ./__tt_dti_fa_color_ts_ns_wt -a ./__tt_dti_fa_color_ts_ns+orig -expr 'min(1,(a/71.627998))'
++ 3dcalc: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: A cast of thousands
++ Output dataset ././__tt_dti_fa_color_ts_ns_wt+orig.BRIK
#++ Aligning anat data to epi data
#Script is running (command trimmed):
3dAllineate -lpc -wtprefix ./__tt_aparc.a2009s+aseg_REN_all_ob_al_wtal -weight ./__tt_dti_fa_color_ts_ns_wt+orig -source ./__tt_aparc.a2009s+aseg_REN_all_ob+orig -prefix ./__tt_aparc.a2009s+aseg_REN_all_ob_temp_al -base ./__tt_dti_fa_color_ts_ns+orig -cmass -1Dmatrix_save ./aparc.a2009s+aseg_REN_all_al_e2a_only_mat.aff12.1D -master BASE -mast_dxyz 1.000000 -weight_frac 1.0 -maxrot 6 -maxshf 10 -VERB -warp aff -source_automask+4 -twobest 11 -twopass -VERB -maxrot 45 -maxshf 40 -fineblur 1 -source_automask+2
++ 3dAllineate: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: Zhark the Registrator
*+ WARNING: If you are performing spatial transformations on an oblique dset,
such as ./__tt_dti_fa_color_ts_ns_wt+orig.BRIK,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
See 3dWarp -help for details.
++ Oblique dataset:./__tt_dti_fa_color_ts_ns_wt+orig.BRIK is 5.964928 degrees from plumb.
++ Oblique dataset:./__tt_dti_fa_color_ts_ns+orig.BRIK is 5.964928 degrees from plumb.
++ Source dataset: ./__tt_aparc.a2009s+aseg_REN_all_ob+orig.HEAD
++ Base dataset: ./__tt_dti_fa_color_ts_ns+orig.HEAD
++ Loading datasets
++ 1018263 voxels in -source_automask+2
++ Zero-pad: ybot=1 ytop=0
++ Zero-pad: zbot=1 ztop=0
++ 83035 voxels [17.5%] in weight mask
++ Output dataset ./__tt_aparc.a2009s+aseg_REN_all_ob_al_wtal+orig.BRIK
++ Number of points for matching = 83035
++ NOTE: base and source coordinate systems have different handedness
+ Orientations: base=Left handed (RPI); source=Right handed (RAI)
++ Local correlation: blok type = 'RHDD(7.40821)'
++ base center of mass = 38.585 41.611 31.273 (index)
+ source center of mass = 124.632 150.663 161.098 (index)
+ source-target CM = -11.492 -11.698 -3.974 (xyz)
+ center of mass shifts = -11.492 -11.698 -3.974
++ shift param auto-range: -61.0..38.0 -69.8..46.4 -46.6..38.6
+ Range param#4 [z-angle] = -6.000000 .. 6.000000
+ Range param#5 [x-angle] = -6.000000 .. 6.000000
+ Range param#6 [y-angle] = -6.000000 .. 6.000000
+ Range param#1 [x-shift] = -21.492058 .. -1.492058
+ Range param#2 [y-shift] = -21.698013 .. -1.698013
+ Range param#3 [z-shift] = -13.973885 .. 6.026115
+ Range param#4 [z-angle] = -45.000000 .. 45.000000
+ Range param#5 [x-angle] = -45.000000 .. 45.000000
+ Range param#6 [y-angle] = -45.000000 .. 45.000000
+ Range param#1 [x-shift] = -51.492058 .. 28.507942
+ Range param#2 [y-shift] = -51.698013 .. 28.301987
+ Range param#3 [z-shift] = -43.973885 .. 36.026115
+ 12 free parameters
++ Normalized convergence radius = 0.000468
++ changing output grid spacing to 1.0000 mm
++ OpenMP thread count = 15
++ ======= Allineation of 1 sub-bricks using Local Pearson Correlation Signed =======
+ source mask has 1018263 [out of 22641255] voxels
+ base mask has 119742 [out of 475566] voxels
++ ========== sub-brick #0 ========== [total CPU to here=0.0 s]
++ *** Coarse pass begins ***
+ * Enter alignment setup routine
+ - copying base image
+ - copying source image
+ - Smoothing base; radius=2.22
+ - Smoothing source; radius=2.22
+ !source mask fill: ubot=0 usiz=77
+ - copying weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ - Search for coarse starting parameters
+ 63811 total points stored in 692 'RHDD(7.73427)' bloks
+ - number of free params = 6
+ - Testing (64+61)*64 params:#*[#1=0.00471919] **[#2=0.000668879] **[#3=-0.00676377] *o*[#5=-0.0126895] *..+.-+.o+-o--.*[#55=-0.0153882] *+++*[#181=-0.0171452] *.+-+-oooo*[#2098=-0.0225358] *o+$--+.
+ - best 45 costs found:
0 v=-0.022536: -24.83 1.64 9.36 15.00 -15.00 -30.00 [grid]
1 v=-0.019404: 1.84 -25.03 22.69 -15.00 15.00 30.00 [grid]
2 v=-0.019384: 8.00 -28.37 -1.37 30.54 -19.59 20.03 [rand]
3 v=-0.018200: 1.84 14.97 9.36 -30.00 15.00 30.00 [grid]
4 v=-0.018024: -16.45 -0.51 -27.21 -35.24 13.60 -30.23 [rand]
5 v=-0.017615: 9.48 16.68 28.27 3.65 -28.33 -14.78 [rand]
6 v=-0.017165: -5.68 2.49 25.66 -38.21 -15.41 13.51 [rand]
7 v=-0.017148: 17.52 -38.84 29.64 7.44 27.42 25.63 [rand]
8 v=-0.017145: 1.84 14.97 -17.31 15.00 -15.00 -15.00 [grid]
9 v=-0.016807: 1.84 14.97 9.36 -15.00 30.00 -15.00 [grid]
10 v=-0.016391: 15.17 14.97 22.69 30.00 -15.00 15.00 [grid]
11 v=-0.016366: 4.73 2.41 31.16 -15.74 -34.09 -7.78 [rand]
12 v=-0.016230: -24.83 1.64 22.69 -30.00 -15.00 -15.00 [grid]
13 v=-0.016078: 8.00 4.97 -6.57 30.54 -19.59 20.03 [rand]
14 v=-0.016054: -15.57 -17.92 3.82 -4.32 22.85 -18.95 [rand]
15 v=-0.015962: 15.17 1.64 9.36 -15.00 -30.00 -30.00 [grid]
16 v=-0.015778: -41.28 -0.96 9.99 4.50 6.71 -7.94 [rand]
17 v=-0.015727: 15.64 7.17 23.76 -5.55 17.35 23.42 [rand]
18 v=-0.015637: 2.71 -2.24 0.86 -15.99 -13.53 -29.93 [rand]
19 v=-0.015555: 1.84 14.97 22.69 -15.00 -15.00 -15.00 [grid]
20 v=-0.015518: 4.65 -2.23 20.38 20.99 15.73 -16.09 [rand]
21 v=-0.015418: 8.29 -28.45 -21.65 2.96 2.59 18.65 [rand]
22 v=-0.015388: 1.84 -25.03 -17.31 15.00 -15.00 -15.00 [grid]
23 v=-0.015121: 15.17 -38.36 9.36 -30.00 30.00 -30.00 [grid]
24 v=-0.015068: -24.83 -38.36 9.36 -30.00 -30.00 -30.00 [grid]
25 v=-0.015019: 15.17 1.64 22.69 15.00 15.00 30.00 [grid]
26 v=-0.014990: 15.17 14.97 22.69 15.00 -30.00 -15.00 [grid]
27 v=-0.014860: -25.52 -27.42 10.69 24.25 -37.55 4.41 [rand]
28 v=-0.014852: 15.17 1.64 9.36 -30.00 30.00 15.00 [grid]
29 v=-0.014826: 15.17 -25.03 9.36 -30.00 30.00 -30.00 [grid]
30 v=-0.014823: 2.54 4.02 10.69 24.25 -37.55 -4.41 [rand]
31 v=-0.014815: -24.65 26.19 33.22 -14.03 -8.39 -25.20 [rand]
32 v=-0.014809: -24.83 14.97 -17.31 -30.00 -15.00 -30.00 [grid]
33 v=-0.014793: -24.83 1.64 9.36 -15.00 -30.00 -15.00 [grid]
34 v=-0.014759: -6.54 -22.88 19.26 -35.24 -13.60 -30.23 [rand]
35 v=-0.014755: 13.20 -16.31 12.41 -8.97 18.72 30.56 [rand]
36 v=-0.014729: 12.71 -22.04 0.55 -27.51 29.30 27.65 [rand]
37 v=-0.014702: 5.37 6.89 10.48 -19.57 -37.09 -16.59 [rand]
38 v=-0.014636: 15.17 1.64 22.69 -15.00 30.00 15.00 [grid]
39 v=-0.014634: -26.71 -48.13 -14.48 3.49 -11.25 -35.41 [rand]
40 v=-0.014625: -38.16 -25.03 -30.64 15.00 15.00 -15.00 [grid]
41 v=-0.014547: 1.84 14.97 22.69 -15.00 -15.00 30.00 [grid]
42 v=-0.014506: 1.84 1.64 9.36 15.00 -30.00 30.00 [grid]
43 v=-0.014465: -24.83 -38.36 9.36 15.00 30.00 -30.00 [grid]
44 v=-0.014458: 15.17 1.64 22.69 30.00 -30.00 15.00 [grid]
*[#8012=-0.0231938] *[#8014=-0.0235016] *[#8016=-0.0236742] *[#8017=-0.0239727] *[#8018=-0.0242408] *[#8020=-0.0248683] *[#8054=-0.0253632] *[#8056=-0.0261143] *[#8058=-0.0268665] *[#8339=-0.0269286] *[#8341=-0.0273273] *[#8342=-0.0273879] *[#8344=-0.0274693] *[#9374=-0.0275237] *[#9375=-0.0279147] *[#9380=-0.0284446] *[#9381=-0.0293261] *[#9382=-0.0295928] *[#9383=-0.0307181] *[#9385=-0.030963] *[#9386=-0.0311503] *[#9389=-0.0313224] *[#9391=-0.0314866] *[#9392=-0.0315236] + - costs of the above after a little optimization:
0 v=-0.024868: -23.92 1.04 8.93 15.07 -14.99 -29.54 [grid]
1 v=-0.026866: 2.90 -24.00 24.62 -14.78 15.05 30.77 [grid]
2 v=-0.021172: 7.66 -28.98 -1.11 29.83 -19.93 19.78 [rand]
3 v=-0.023299: 1.78 15.57 5.97 -32.23 13.32 28.63 [grid]
4 v=-0.019653: -16.38 -0.09 -27.04 -35.01 13.42 -30.49 [rand]
5 v=-0.025574: 8.95 16.08 30.85 1.99 -28.75 -14.59 [rand]
6 v=-0.025849: -6.75 -4.00 26.73 -43.99 -16.58 10.81 [rand]
7 v=-0.020187: 17.90 -39.85 29.88 7.57 27.65 26.99 [rand]
8 v=-0.018988: 1.33 14.82 -17.31 15.09 -10.69 -15.00 [grid]
9 v=-0.021262: 2.65 13.07 8.75 -15.08 28.30 -14.96 [grid]
10 v=-0.027469: 12.41 14.42 19.99 28.81 -18.37 10.68 [grid]
11 v=-0.019326: 2.27 1.78 30.99 -16.66 -33.67 -9.02 [rand]
12 v=-0.019453: -24.49 1.65 23.70 -30.13 -14.96 -14.61 [grid]
13 v=-0.018888: 7.58 4.17 -6.99 30.39 -20.59 19.99 [rand]
14 v=-0.022777: -16.47 -18.60 3.13 -3.89 26.64 -19.49 [rand]
15 v=-0.017029: 14.71 -2.32 9.41 -15.05 -29.51 -29.87 [grid]
16 v=-0.023860: -41.03 -0.27 11.58 4.58 6.35 -9.07 [rand]
17 v=-0.016762: 15.50 6.94 23.56 -5.54 17.36 23.66 [rand]
18 v=-0.019954: 2.79 2.20 1.10 -15.40 -13.40 -29.62 [rand]
19 v=-0.021719: 1.74 14.81 23.57 -12.08 -14.58 -13.91 [grid]
20 v=-0.017193: 5.08 -2.28 20.44 21.54 15.50 -15.41 [rand]
21 v=-0.016782: 8.31 -28.02 -21.65 3.45 2.57 19.10 [rand]
22 v=-0.019968: 2.36 -23.37 -16.60 15.34 -15.47 -15.08 [grid]
23 v=-0.019785: 16.57 -33.74 9.65 -29.13 30.22 -28.17 [grid]
24 v=-0.019569: -25.26 -37.85 7.23 -34.04 -30.60 -30.61 [grid]
25 v=-0.025539: 14.59 0.44 21.99 18.43 13.60 29.27 [grid]
26 v=-0.019970: 14.61 14.65 22.01 14.39 -25.66 -16.04 [grid]
27 v=-0.017985: -26.51 -27.74 10.43 24.43 -38.32 4.47 [rand]
28 v=-0.021026: 15.02 1.66 9.01 -29.85 29.56 19.32 [grid]
29 v=-0.018131: 15.13 -25.31 7.60 -30.54 28.70 -32.71 [grid]
30 v=-0.020603: 3.13 -1.39 10.58 24.89 -37.71 -3.50 [rand]
31 v=-0.015345: -24.64 26.48 33.24 -13.77 -8.13 -25.45 [rand]
32 v=-0.015142: -24.83 15.37 -17.30 -30.00 -15.00 -29.99 [grid]
33 v=-0.019544: -24.97 2.30 7.88 -15.68 -29.42 -14.58 [grid]
34 v=-0.026107: -5.78 -18.96 19.06 -34.83 -13.83 -31.39 [rand]
35 v=-0.021929: 15.14 -19.27 13.06 -9.76 22.97 31.13 [rand]
36 v=-0.022851: 17.16 -21.77 -0.07 -27.65 29.69 28.64 [rand]
37 v=-0.015690: 5.37 7.27 10.46 -19.58 -36.63 -16.60 [rand]
38 v=-0.021913: 18.37 3.37 20.20 -18.30 29.07 14.52 [grid]
39 v=-0.021658: -28.84 -48.79 -14.22 7.68 -11.70 -37.10 [rand]
40 v=-0.017059: -38.96 -25.39 -30.22 14.18 14.87 -14.79 [grid]
41 v=-0.026412: 2.13 18.12 23.13 -16.47 -16.13 30.90 [grid]
42 v=-0.020362: 1.17 2.47 10.66 18.15 -30.21 29.98 [grid]
43 v=-0.019816: -22.15 -38.31 9.11 14.26 30.18 -29.96 [grid]
*44 v=-0.031524: 15.51 9.76 26.68 34.72 -36.23 16.15 [grid]
+ - save #44 for twobest
+ - save #10 for twobest
+ - save # 1 for twobest
+ - save #41 for twobest
+ - save #34 for twobest
+ - save # 6 for twobest
+ - save # 5 for twobest
+ - save #25 for twobest
+ - save # 0 for twobest
+ - save #16 for twobest
+ - save # 3 for twobest
+ - save #36 for twobest
+ - save #14 for twobest
+ - save #35 for twobest
+ - save #38 for twobest
+ - save #19 for twobest
+ - save #39 for twobest
+ - save # 9 for twobest
+ - save # 2 for twobest
+ - save #28 for twobest
+ - save #30 for twobest
+ - save #42 for twobest
+ - Coarse startup search net CPU time = 0.0 s
++ Start refinement #1 on 12 coarse parameter sets
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.73
+ - Smoothing source; radius=1.73
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ 64586 total points stored in 736 'RHDD(7.60708)' bloks
+ - param set #1 has cost=-0.026479
+ -- Parameters = 16.2215 8.7457 26.3776 34.5054 -36.0299 16.7043 1.0155 1.0057 1.0049 0.0015 0.0034 0.0043
+ - param set #2 has cost=-0.022746
+ -- Parameters = 12.1852 15.0102 20.1542 29.4408 -18.2730 9.7535 1.0002 0.9999 1.0111 0.0004 -0.0019 0.0007
+ - param set #3 has cost=-0.026379
+ -- Parameters = 3.3124 -25.1277 24.8633 -14.8001 16.7320 31.5535 1.0007 1.0003 1.0030 0.0028 -0.0013 0.0013
+ - param set #4 has cost=-0.024786
+ -- Parameters = 2.2224 18.4242 23.8774 -16.2982 -16.9026 31.2338 0.9979 1.0173 0.9992 0.0000 -0.0009 0.0012
+ - param set #5 has cost=-0.024137
+ -- Parameters = -4.6498 -18.4775 19.0419 -34.6823 -14.2764 -31.0895 0.9899 0.9954 0.9999 0.0085 -0.0013 -0.0013
+ - param set #6 has cost=-0.024387
+ -- Parameters = -6.7519 -3.5739 26.8845 -43.3186 -16.8582 10.9768 1.0001 1.0002 0.9999 0.0016 -0.0003 0.0102
+ - param set #7 has cost=-0.022045
+ -- Parameters = 8.6976 16.0298 30.9245 2.0342 -28.4244 -14.7493 1.0000 0.9998 1.0000 0.0007 -0.0001 0.0008
+ - param set #8 has cost=-0.029658
+ -- Parameters = 14.4628 1.2380 20.5142 17.4061 12.8884 29.8108 1.0195 1.0072 1.0025 0.0040 -0.0027 0.0025
+ - param set #9 has cost=-0.023492
+ -- Parameters = -22.3215 -3.0161 9.2411 14.0489 -15.4619 -28.5935 0.9974 1.0075 1.0034 0.0021 0.0003 -0.0007
+ - param set #10 has cost=-0.015754
+ -- Parameters = -41.1503 -0.9794 12.0651 4.4159 6.2924 -9.3190 0.9993 1.0170 0.9989 -0.0010 -0.0011 -0.0001
+ - param set #11 has cost=-0.024567
+ -- Parameters = 2.1696 14.4887 5.8095 -32.2792 13.0661 27.7162 0.9997 0.9934 1.0022 0.0005 0.0015 0.0021
+ - param set #12 has cost=-0.020996
+ -- Parameters = -7.4202 -19.5787 -4.5353 -2.0793 1.1457 -0.4236 1.0020 1.0088 1.0131 -0.0072 -0.0001 0.0085
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ --- dist(#2,#1) = 0.544
+ --- dist(#3,#1) = 0.358
+ --- dist(#4,#1) = 0.374
+ --- dist(#5,#1) = 0.552
+ --- dist(#6,#1) = 0.675
+ --- dist(#7,#1) = 0.677
+ --- dist(#8,#1) = 0.649
+ --- dist(#9,#1) = 0.346
+ --- dist(#10,#1) = 0.495
+ --- dist(#11,#1) = 0.336
+ --- dist(#12,#1) = 0.695
++ Start refinement #2 on 12 coarse parameter sets
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.34
+ - Smoothing source; radius=1.34
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ 64353 total points stored in 748 'RHDD(7.52912)' bloks
+ - param set #1 has cost=-0.027788
+ -- Parameters = 14.0970 0.8611 20.7120 16.8405 12.7571 29.4767 1.0321 0.9980 1.0014 0.0070 -0.0014 0.0001
+ - param set #2 has cost=-0.023240
+ -- Parameters = 16.5967 8.3522 26.5036 34.0808 -36.0693 16.6212 1.0164 1.0054 1.0015 0.0012 0.0041 0.0045
+ - param set #3 has cost=-0.023370
+ -- Parameters = 3.7492 -25.8706 25.2041 -15.2226 16.5056 31.8804 0.9964 1.0035 0.9988 0.0104 -0.0072 -0.0018
+ - param set #4 has cost=-0.022504
+ -- Parameters = 2.1974 18.3549 24.2592 -16.5142 -17.1367 31.3686 1.0096 1.0161 1.0003 -0.0026 -0.0024 0.0024
+ - param set #5 has cost=-0.021890
+ -- Parameters = 2.3203 14.2823 5.8535 -32.1962 13.1184 27.6574 1.0007 0.9933 1.0032 0.0009 0.0017 0.0088
+ - param set #6 has cost=-0.023298
+ -- Parameters = -6.1952 -3.2403 26.6734 -42.8086 -17.8344 10.9566 1.0175 0.9985 1.0049 0.0006 -0.0018 0.0117
+ - param set #7 has cost=-0.020048
+ -- Parameters = -4.8366 -18.8258 18.6913 -34.4418 -14.2596 -31.3652 0.9887 0.9955 1.0006 0.0086 -0.0013 -0.0012
+ - param set #8 has cost=-0.020654
+ -- Parameters = -22.1182 -2.8413 9.1909 14.0488 -15.4422 -28.5306 0.9975 1.0173 1.0038 0.0023 0.0004 -0.0005
+ - param set #9 has cost=-0.022256
+ -- Parameters = 12.0172 15.0750 19.9304 29.3012 -18.1258 9.2558 1.0011 0.9924 1.0114 -0.0004 -0.0028 0.0024
+ - param set #10 has cost=-0.020049
+ -- Parameters = 8.1666 15.4000 31.2752 2.0698 -27.9150 -15.4678 1.0028 1.0240 0.9932 -0.0034 -0.0092 -0.0127
+ - param set #11 has cost=-0.022165
+ -- Parameters = -7.5335 -20.0728 -4.4943 -1.8965 1.5048 -3.0435 1.0033 1.0020 1.0148 -0.0073 0.0019 0.0092
+ - param set #12 has cost=-0.013957
+ -- Parameters = -40.8313 -0.8413 12.0765 4.8930 5.2536 -9.4364 0.9967 1.0269 0.9977 -0.0020 -0.0017 -0.0020
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ --- dist(#2,#1) = 0.356
+ --- dist(#3,#1) = 0.663
+ --- dist(#4,#1) = 0.543
+ --- dist(#5,#1) = 0.371
+ --- dist(#6,#1) = 0.343
+ --- dist(#7,#1) = 0.361
+ --- dist(#8,#1) = 0.545
+ --- dist(#9,#1) = 0.645
+ --- dist(#10,#1) = 0.499
+ --- dist(#11,#1) = 0.676
+ --- dist(#12,#1) = 0.687
++ Start refinement #3 on 12 coarse parameter sets
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.05
+ - Smoothing source; radius=1.05
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ 63291 total points stored in 742 'RHDD(7.48157)' bloks
+ - param set #1 has cost=-0.024336
+ -- Parameters = 14.1187 0.8828 20.7434 16.5813 12.8460 30.0161 1.0357 0.9983 1.0117 0.0054 -0.0068 -0.0081
+ - param set #2 has cost=-0.022973
+ -- Parameters = 4.4777 -25.9934 25.8420 -15.3839 16.3332 32.4821 1.0014 1.0062 0.9910 0.0057 -0.0089 -0.0112
+ - param set #3 has cost=-0.018197
+ -- Parameters = -5.7590 -3.3671 26.8432 -42.5681 -17.7782 11.3212 1.0256 0.9980 1.0053 0.0001 -0.0020 0.0117
+ - param set #4 has cost=-0.020662
+ -- Parameters = 16.4958 8.3483 26.4539 34.2508 -36.0745 16.6056 1.0161 0.9974 1.0024 0.0012 0.0044 0.0048
+ - param set #5 has cost=-0.018953
+ -- Parameters = 2.1706 18.4948 24.3577 -16.3990 -17.2723 31.3160 1.0099 1.0162 1.0001 0.0021 -0.0026 0.0026
+ - param set #6 has cost=-0.020637
+ -- Parameters = 11.9027 15.0777 19.8916 29.3447 -18.1611 9.1239 1.0000 0.9916 1.0096 -0.0009 -0.0035 0.0066
+ - param set #7 has cost=-0.024130
+ -- Parameters = -8.5786 -20.8752 -4.3985 -2.9652 2.0926 -3.3924 0.9729 1.0041 1.0088 -0.0167 0.0035 0.0109
+ - param set #8 has cost=-0.020442
+ -- Parameters = 1.7470 13.9685 5.7909 -32.2941 13.3299 27.6914 0.9874 0.9996 1.0080 0.0024 -0.0008 0.0108
+ - param set #9 has cost=-0.019524
+ -- Parameters = -22.0544 -3.0124 8.9268 14.7008 -15.5012 -28.4252 0.9918 1.0232 0.9959 0.0075 0.0135 0.0015
+ - param set #10 has cost=-0.018739
+ -- Parameters = 8.1731 15.1613 31.2958 2.1626 -27.7801 -15.7908 1.0028 1.0238 0.9930 -0.0030 -0.0040 -0.0125
+ - param set #11 has cost=-0.019804
+ -- Parameters = -4.9883 -18.8266 18.4915 -34.3060 -14.0771 -31.3249 0.9879 0.9953 1.0148 0.0091 0.0004 -0.0020
+ - param set #12 has cost=-0.013710
+ -- Parameters = -41.2379 -0.8433 11.9833 4.8082 5.9352 -9.4359 0.9936 1.0251 0.9917 -0.0126 -0.0009 -0.0075
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ --- dist(#2,#1) = 0.371
+ --- dist(#3,#1) = 0.355
+ --- dist(#4,#1) = 0.544
+ --- dist(#5,#1) = 0.345
+ --- dist(#6,#1) = 0.543
+ --- dist(#7,#1) = 0.682
+ --- dist(#8,#1) = 0.649
+ --- dist(#9,#1) = 0.366
+ --- dist(#10,#1) = 0.509
+ --- dist(#11,#1) = 0.657
+ --- dist(#12,#1) = 0.692
+ - Total coarse refinement net CPU time = 0.0 s; 2960 funcs
++ *** Fine pass begins ***
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.00
+ - Smoothing source; radius=1.00
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ * Exit alignment setup routine
++ Picking best parameter set out of 13 cases
+ 63170 total points stored in 740 'RHDD(7.4754)' bloks
+ - cost(#1)=-0.023757 *
+ -- Parameters = 14.1187 0.8828 20.7434 16.5813 12.8460 30.0161 1.0357 0.9983 1.0117 0.0054 -0.0068 -0.0081
+ - cost(#2)=-0.023130
+ -- Parameters = -8.5786 -20.8752 -4.3985 -2.9652 2.0926 -3.3924 0.9729 1.0041 1.0088 -0.0167 0.0035 0.0109
+ - cost(#3)=-0.021934
+ -- Parameters = 4.4777 -25.9934 25.8420 -15.3839 16.3332 32.4821 1.0014 1.0062 0.9910 0.0057 -0.0089 -0.0112
+ - cost(#4)=-0.020620
+ -- Parameters = 16.4958 8.3483 26.4539 34.2508 -36.0745 16.6056 1.0161 0.9974 1.0024 0.0012 0.0044 0.0048
+ - cost(#5)=-0.020130
+ -- Parameters = 11.9027 15.0777 19.8916 29.3447 -18.1611 9.1239 1.0000 0.9916 1.0096 -0.0009 -0.0035 0.0066
+ - cost(#6)=-0.019893
+ -- Parameters = 1.7470 13.9685 5.7909 -32.2941 13.3299 27.6914 0.9874 0.9996 1.0080 0.0024 -0.0008 0.0108
+ - cost(#7)=-0.019779
+ -- Parameters = -4.9883 -18.8266 18.4915 -34.3060 -14.0771 -31.3249 0.9879 0.9953 1.0148 0.0091 0.0004 -0.0020
+ - cost(#8)=-0.019722
+ -- Parameters = -22.0544 -3.0124 8.9268 14.7008 -15.5012 -28.4252 0.9918 1.0232 0.9959 0.0075 0.0135 0.0015
+ - cost(#9)=-0.018865
+ -- Parameters = 2.1706 18.4948 24.3577 -16.3990 -17.2723 31.3160 1.0099 1.0162 1.0001 0.0021 -0.0026 0.0026
+ - cost(#10)=-0.019543
+ -- Parameters = 8.1731 15.1613 31.2958 2.1626 -27.7801 -15.7908 1.0028 1.0238 0.9930 -0.0030 -0.0040 -0.0125
+ - cost(#11)=-0.017782
+ -- Parameters = -5.7590 -3.3671 26.8432 -42.5681 -17.7782 11.3212 1.0256 0.9980 1.0053 0.0001 -0.0020 0.0117
+ - cost(#12)=-0.014161
+ -- Parameters = -41.2379 -0.8433 11.9833 4.8082 5.9352 -9.4359 0.9936 1.0251 0.9917 -0.0126 -0.0009 -0.0075
+ - cost(#13)=0.005226
+ -- Parameters = -11.4921 -11.6980 -3.9739 0.0000 0.0000 0.0000 1.0000 1.0000 1.0000 0.0000 0.0000 0.0000
+ -num_rtb 99 ==> refine all 13 cases
+ - cost(#1)=-0.024418 *
+ -- Parameters = 14.3779 0.8722 21.1826 16.3852 12.9293 30.2378 1.0375 0.9970 1.0026 0.0056 -0.0064 -0.0089
+ - cost(#2)=-0.024645 *
+ -- Parameters = -8.2545 -20.8388 -3.7363 -3.5421 2.3906 -3.1639 0.9712 0.9988 1.0080 -0.0192 0.0081 0.0109
+ - cost(#3)=-0.023247
+ -- Parameters = 4.5512 -25.6708 26.0902 -15.6811 16.3145 32.6327 1.0041 1.0207 0.9845 0.0053 -0.0099 -0.0085
+ - cost(#4)=-0.020928
+ -- Parameters = 16.6291 8.3561 26.4100 34.1161 -36.0983 16.5971 1.0141 0.9948 1.0041 -0.0007 0.0039 0.0051
+ - cost(#5)=-0.020272
+ -- Parameters = 11.8949 15.0997 19.9117 29.2718 -18.1548 9.0607 1.0019 0.9909 1.0086 -0.0005 -0.0037 0.0080
+ - cost(#6)=-0.021048
+ -- Parameters = 1.4116 13.4820 5.8495 -31.9231 13.7610 27.6395 0.9867 1.0015 1.0182 0.0032 -0.0007 0.0110
+ - cost(#7)=-0.020035
+ -- Parameters = -4.9471 -18.8311 18.3750 -34.2716 -14.1094 -31.2946 0.9884 0.9946 1.0191 0.0095 0.0002 -0.0026
+ - cost(#8)=-0.019934
+ -- Parameters = -22.1272 -3.1214 8.8960 14.7712 -15.4499 -28.5095 0.9919 1.0247 0.9972 0.0082 0.0134 -0.0009
+ - cost(#9)=-0.019515
+ -- Parameters = 2.1792 18.3929 24.5164 -16.2633 -17.2139 31.6223 1.0077 1.0185 1.0095 0.0026 -0.0022 0.0033
+ - cost(#10)=-0.019823
+ -- Parameters = 8.1269 15.0958 31.3265 2.1939 -27.7889 -15.8520 1.0033 1.0236 0.9935 -0.0027 -0.0007 -0.0123
+ - cost(#11)=-0.018110
+ -- Parameters = -5.5245 -3.4395 26.8576 -42.4438 -17.5436 11.5284 1.0273 0.9973 1.0063 0.0020 -0.0005 0.0109
+ - cost(#12)=-0.014392
+ -- Parameters = -41.2188 -0.8423 11.9957 4.6287 6.0137 -9.4365 0.9922 1.0254 0.9918 -0.0167 -0.0009 -0.0080
+ - cost(#13)=-0.030355 *
+ -- Parameters = -8.9538 -8.1442 -3.9384 1.4917 -3.2794 -6.4530 0.9953 0.9972 1.0017 0.0050 0.0052 0.0009
+ - case #13 is now the best
+ - Initial cost = -0.030355
+ - Initial fine Parameters = -8.9538 -8.1442 -3.9384 1.4917 -3.2794 -6.4530 0.9953 0.9972 1.0017 0.0050 0.0052 0.0009
+ - Finalish cost = -0.031012 ; 267 funcs
+ - Final cost = -0.031145 ; 184 funcs
+ Final fine fit Parameters:
x-shift=-8.8944 y-shift=-8.0605 z-shift=-4.2098
z-angle= 1.5925 x-angle=-3.4289 y-angle=-6.3804
x-scale= 0.9928 y-scale= 0.9913 z-scale= 1.0066
y/x-shear= 0.0083 z/x-shear=-0.0005 z/y-shear= 0.0011
+ - Fine net CPU time = 0.0 s
++ Computing output image
++ image warp: parameters = -8.8944 -8.0605 -4.2098 1.5925 -3.4289 -6.3804 0.9928 0.9913 1.0066 0.0083 -0.0005 0.0011
++ Output dataset ./__tt_aparc.a2009s+aseg_REN_all_ob_temp_al+orig.BRIK
++ Wrote -1Dmatrix_save ./aparc.a2009s+aseg_REN_all_al_e2a_only_mat.aff12.1D
++ 3dAllineate: total CPU time = 0.0 sec Elapsed = 38.9
++ ###########################################################
++ # Please check results visually for alignment quality #
++ ###########################################################
++ # '-autoweight' is recommended when using -lpc or -lpa #
++ # If your results are not good, please try again. #
++ ###########################################################
#Script is running (command trimmed):
cat_matvec -ONELINE ./aparc.a2009s+aseg_REN_all_al_e2a_only_mat.aff12.1D ./__tt_aparc.a2009s+aseg_REN_all_obla2e_mat.1D -I > ./aparc.a2009s+aseg_REN_all_al_mat.aff12.1D
#++ Combining anat to epi and oblique transformations
#Script is running (command trimmed):
3dAllineate -base ./__tt_dti_fa_color_ts_ns+orig -1Dmatrix_apply ./aparc.a2009s+aseg_REN_all_al_mat.aff12.1D -prefix ./aparc.a2009s+aseg_REN_all_al -input ./__tt_aparc.a2009s+aseg_REN_all+orig -master BASE -mast_dxyz 1.000000 -weight_frac 1.0 -maxrot 6 -maxshf 10 -VERB -warp aff -source_automask+4 -twobest 11 -twopass -VERB -maxrot 45 -maxshf 40 -fineblur 1 -source_automask+2
++ 3dAllineate: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: Zhark the Registrator
*+ WARNING: If you are performing spatial transformations on an oblique dset,
such as ./__tt_dti_fa_color_ts_ns+orig.BRIK,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
See 3dWarp -help for details.
++ Oblique dataset:./__tt_dti_fa_color_ts_ns+orig.BRIK is 5.964928 degrees from plumb.
++ Source dataset: ./__tt_aparc.a2009s+aseg_REN_all+orig.HEAD
++ Base dataset: ./__tt_dti_fa_color_ts_ns+orig.HEAD
++ Loading datasets
+ Range param#4 [z-angle] = -6.000000 .. 6.000000
+ Range param#5 [x-angle] = -6.000000 .. 6.000000
+ Range param#6 [y-angle] = -6.000000 .. 6.000000
+ Range param#1 [x-shift] = -10.000000 .. 10.000000
+ Range param#2 [y-shift] = -10.000000 .. 10.000000
+ Range param#3 [z-shift] = -10.000000 .. 10.000000
+ Range param#4 [z-angle] = -45.000000 .. 45.000000
+ Range param#5 [x-angle] = -45.000000 .. 45.000000
+ Range param#6 [y-angle] = -45.000000 .. 45.000000
+ Range param#1 [x-shift] = -40.000000 .. 40.000000
+ Range param#2 [y-shift] = -40.000000 .. 40.000000
+ Range param#3 [z-shift] = -40.000000 .. 40.000000
++ changing output grid spacing to 1.0000 mm
++ OpenMP thread count = 15
++ ========== Applying transformation to 1 sub-bricks ==========
++ ========== sub-brick #0 ========== [total CPU to here=0.0 s]
+ * Enter alignment setup routine
+ - copying base image
+ - copying source image
+ - no weight image
+ - using 11 points from base image [use_all=0]
+ * Exit alignment setup routine
++ using -1Dmatrix_apply
++ Computing output image
++ image warp: parameters = 0.9804 -0.0128 0.1546 39.3888 0.1564 -0.0376 -0.9936 163.6616 0.0103 0.9909 -0.0384 36.1785
++ Output dataset ./aparc.a2009s+aseg_REN_all_al+orig.BRIK
++ 3dAllineate: total CPU time = 0.0 sec Elapsed = 0.7
++ ###########################################################
#++ Creating final output: anat data aligned to epi
# copy is not necessary
#++ Saving history
#Script is running (command trimmed):
3dNotes -h "align_epi_anat.py -anat aparc.a2009s+aseg_REN_all.nii.gz -epi \
dti_fa_color+orig -epi_base 0 -anat_has_skull no -epi_strip 3dAutomask \
-volreg off -tshift off -giant_move" \
./aparc.a2009s+aseg_REN_all_al+orig
#++ Removing all the temporary files
#Script is running:
\rm -f ./__tt_dti_fa_color*
#Script is running:
\rm -f ./__tt_aparc.a2009s+aseg_REN_all*
# Finished alignment successfully
I am doing registration between two datasets, that is, the DTI dataset and a parcellated dataset.
Here are the scripts I used here (dti_fa_color.nii.gz is the DTI dataset, and aparc.a2009s+aseg_REN_all.nii is the parcellated dataset) :
3dcalc -a dti_fa_color.nii.gz -expr 'a' -prefix dti_fa_color
align_epi_anat.py -anat aparc.a2009s+aseg_REN_all.nii.gz -epi dti_fa_color+orig -epi_base 0 -anat_has_skull no -epi_strip 3dAutomask -volreg off -tshift off -big_move
However, after running the scripts, I got the following 5 warnings. The main problem lies in that:
If you are performing spatial transformations on an oblique dset,
such as .......,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
I have seen some similar questions in this forum, but I have not solved my problem. Although these are some warnings instead of errors, the registration result is bad. Could you please give me some suggestions. Many thanks!
The version of AFNI I used is --- binary linux_ubuntu_16_64: Jun 6 2017 (Version AFNI_17.1.09)
Here are the results I got:
align_epi_anat.py -anat aparc.a2009s+aseg_REN_all.nii.gz -epi dti_fa_co
lor+orig -epi_base 0 -anat_has_skull no -epi_strip 3dAutomask -volreg off -tshift off -giant_move
#++ align_epi_anat version: 1.57
#++ turning off volume registration
#Script is running (command trimmed):
3dAttribute DELTA ./dti_fa_color+orig
#Script is running (command trimmed):
3dAttribute DELTA ./dti_fa_color+orig
#Script is running (command trimmed):
3dAttribute DELTA ./aparc.a2009s+aseg_REN_all.nii.gz
#++ Multi-cost is lpc
#++ Removing all the temporary files
#Script is running:
\rm -f ./__tt_dti_fa_color*
#Script is running:
\rm -f ./__tt_aparc.a2009s+aseg_REN_all*
#Script is running (command trimmed):
3dcopy ./aparc.a2009s+aseg_REN_all.nii.gz ./__tt_aparc.a2009s+aseg_REN_all+orig
++ 3dcopy: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
#Script is running (command trimmed):
3dinfo ./__tt_aparc.a2009s+aseg_REN_all+orig | \grep 'Data Axes Tilt:'|\grep 'Oblique'
#++ Dataset /media/raymondlab/DATA/Yuqi/freesurfer_subjects/pure_T1/0cyf/SUMA/__tt_aparc.a2009s+aseg_REN_all+orig is not oblique
#Script is running (command trimmed):
3dinfo ./dti_fa_color+orig | \grep 'Data Axes Tilt:'|\grep 'Oblique'
#++ Dataset /media/raymondlab/DATA/Yuqi/freesurfer_subjects/pure_T1/0cyf/SUMA/dti_fa_color+orig is ***oblique****
#Script is running (command trimmed):
3dAttribute DELTA ./__tt_aparc.a2009s+aseg_REN_all+orig
#++ Spacing for anat to oblique epi alignment is 1.000000
#++ Matching obliquity of anat to epi
#Script is running (command trimmed):
3dWarp -verb -card2oblique ./dti_fa_color+orig -prefix ./__tt_aparc.a2009s+aseg_REN_all_ob -newgrid 1.000000 ./__tt_aparc.a2009s+aseg_REN_all+orig | \grep -A 4 '# mat44 Obliquity Transformation ::' > ./__tt_aparc.a2009s+aseg_REN_all_obla2e_mat.1D
++ 3dWarp: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: RW Cox
#++ using 0th sub-brick because only one found
#Script is running (command trimmed):
3dbucket -prefix ./__tt_dti_fa_color_ts ./dti_fa_color+orig'[0]'
++ 3dbucket: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
#++ removing skull or area outside brain
#Script is running (command trimmed):
3dAutomask -apply_prefix ./__tt_dti_fa_color_ts_ns ./__tt_dti_fa_color_ts+orig
++ 3dAutomask: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: Emperor Zhark
*+ WARNING: If you are performing spatial transformations on an oblique dset,
such as ./__tt_dti_fa_color_ts+orig.BRIK,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
See 3dWarp -help for details.
++ Oblique dataset:./__tt_dti_fa_color_ts+orig.BRIK is 5.964928 degrees from plumb.
++ Loading dataset ./__tt_dti_fa_color_ts+orig
++ Forming automask
+ Fixed clip level = 14.898818
+ Used gradual clip level = 13.122265 .. 17.882113
+ Number voxels above clip level = 106456
+ Clustering voxels ...
+ Largest cluster has 104109 voxels
+ Clustering voxels ...
+ Largest cluster has 78274 voxels
+ Filled 4709 voxels in small holes; now have 82983 voxels
+ Filled 147 voxels in large holes; now have 83130 voxels
+ Clustering voxels ...
+ Largest cluster has 82934 voxels
+ Clustering non-brain voxels ...
+ Clustering voxels ...
+ Largest cluster has 380281 voxels
+ Mask now has 83039 voxels
++ 83039 voxels in the mask [out of 463320: 17.92%]
++ first 4 x-planes are zero [from R]
++ last 4 x-planes are zero [from L]
++ first 3 y-planes are zero [from P]
++ last 7 y-planes are zero [from A]
++ first 3 z-planes are zero [from I]
++ last 5 z-planes are zero [from S]
++ applying mask to original data
++ Writing masked data
++ CPU time = 0.000000 sec
#++ Computing weight mask
#Script is running (command trimmed):
3dBrickStat -automask -percentile 90.000000 1 90.000000 ./__tt_dti_fa_color_ts_ns+orig
#++ Applying threshold of 71.627998 on /media/raymondlab/DATA/Yuqi/freesurfer_subjects/pure_T1/0cyf/SUMA/__tt_dti_fa_color_ts_ns+orig
#Script is running (command trimmed):
3dcalc -datum float -prefix ./__tt_dti_fa_color_ts_ns_wt -a ./__tt_dti_fa_color_ts_ns+orig -expr 'min(1,(a/71.627998))'
++ 3dcalc: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: A cast of thousands
++ Output dataset ././__tt_dti_fa_color_ts_ns_wt+orig.BRIK
#++ Aligning anat data to epi data
#Script is running (command trimmed):
3dAllineate -lpc -wtprefix ./__tt_aparc.a2009s+aseg_REN_all_ob_al_wtal -weight ./__tt_dti_fa_color_ts_ns_wt+orig -source ./__tt_aparc.a2009s+aseg_REN_all_ob+orig -prefix ./__tt_aparc.a2009s+aseg_REN_all_ob_temp_al -base ./__tt_dti_fa_color_ts_ns+orig -cmass -1Dmatrix_save ./aparc.a2009s+aseg_REN_all_al_e2a_only_mat.aff12.1D -master BASE -mast_dxyz 1.000000 -weight_frac 1.0 -maxrot 6 -maxshf 10 -VERB -warp aff -source_automask+4 -twobest 11 -twopass -VERB -maxrot 45 -maxshf 40 -fineblur 1 -source_automask+2
++ 3dAllineate: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: Zhark the Registrator
*+ WARNING: If you are performing spatial transformations on an oblique dset,
such as ./__tt_dti_fa_color_ts_ns_wt+orig.BRIK,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
See 3dWarp -help for details.
++ Oblique dataset:./__tt_dti_fa_color_ts_ns_wt+orig.BRIK is 5.964928 degrees from plumb.
++ Oblique dataset:./__tt_dti_fa_color_ts_ns+orig.BRIK is 5.964928 degrees from plumb.
++ Source dataset: ./__tt_aparc.a2009s+aseg_REN_all_ob+orig.HEAD
++ Base dataset: ./__tt_dti_fa_color_ts_ns+orig.HEAD
++ Loading datasets
++ 1018263 voxels in -source_automask+2
++ Zero-pad: ybot=1 ytop=0
++ Zero-pad: zbot=1 ztop=0
++ 83035 voxels [17.5%] in weight mask
++ Output dataset ./__tt_aparc.a2009s+aseg_REN_all_ob_al_wtal+orig.BRIK
++ Number of points for matching = 83035
++ NOTE: base and source coordinate systems have different handedness
+ Orientations: base=Left handed (RPI); source=Right handed (RAI)
++ Local correlation: blok type = 'RHDD(7.40821)'
++ base center of mass = 38.585 41.611 31.273 (index)
+ source center of mass = 124.632 150.663 161.098 (index)
+ source-target CM = -11.492 -11.698 -3.974 (xyz)
+ center of mass shifts = -11.492 -11.698 -3.974
++ shift param auto-range: -61.0..38.0 -69.8..46.4 -46.6..38.6
+ Range param#4 [z-angle] = -6.000000 .. 6.000000
+ Range param#5 [x-angle] = -6.000000 .. 6.000000
+ Range param#6 [y-angle] = -6.000000 .. 6.000000
+ Range param#1 [x-shift] = -21.492058 .. -1.492058
+ Range param#2 [y-shift] = -21.698013 .. -1.698013
+ Range param#3 [z-shift] = -13.973885 .. 6.026115
+ Range param#4 [z-angle] = -45.000000 .. 45.000000
+ Range param#5 [x-angle] = -45.000000 .. 45.000000
+ Range param#6 [y-angle] = -45.000000 .. 45.000000
+ Range param#1 [x-shift] = -51.492058 .. 28.507942
+ Range param#2 [y-shift] = -51.698013 .. 28.301987
+ Range param#3 [z-shift] = -43.973885 .. 36.026115
+ 12 free parameters
++ Normalized convergence radius = 0.000468
++ changing output grid spacing to 1.0000 mm
++ OpenMP thread count = 15
++ ======= Allineation of 1 sub-bricks using Local Pearson Correlation Signed =======
+ source mask has 1018263 [out of 22641255] voxels
+ base mask has 119742 [out of 475566] voxels
++ ========== sub-brick #0 ========== [total CPU to here=0.0 s]
++ *** Coarse pass begins ***
+ * Enter alignment setup routine
+ - copying base image
+ - copying source image
+ - Smoothing base; radius=2.22
+ - Smoothing source; radius=2.22
+ !source mask fill: ubot=0 usiz=77
+ - copying weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ - Search for coarse starting parameters
+ 63811 total points stored in 692 'RHDD(7.73427)' bloks
+ - number of free params = 6
+ - Testing (64+61)*64 params:#*[#1=0.00471919] **[#2=0.000668879] **[#3=-0.00676377] *o*[#5=-0.0126895] *..+.-+.o+-o--.*[#55=-0.0153882] *+++*[#181=-0.0171452] *.+-+-oooo*[#2098=-0.0225358] *o+$--+.
+ - best 45 costs found:
0 v=-0.022536: -24.83 1.64 9.36 15.00 -15.00 -30.00 [grid]
1 v=-0.019404: 1.84 -25.03 22.69 -15.00 15.00 30.00 [grid]
2 v=-0.019384: 8.00 -28.37 -1.37 30.54 -19.59 20.03 [rand]
3 v=-0.018200: 1.84 14.97 9.36 -30.00 15.00 30.00 [grid]
4 v=-0.018024: -16.45 -0.51 -27.21 -35.24 13.60 -30.23 [rand]
5 v=-0.017615: 9.48 16.68 28.27 3.65 -28.33 -14.78 [rand]
6 v=-0.017165: -5.68 2.49 25.66 -38.21 -15.41 13.51 [rand]
7 v=-0.017148: 17.52 -38.84 29.64 7.44 27.42 25.63 [rand]
8 v=-0.017145: 1.84 14.97 -17.31 15.00 -15.00 -15.00 [grid]
9 v=-0.016807: 1.84 14.97 9.36 -15.00 30.00 -15.00 [grid]
10 v=-0.016391: 15.17 14.97 22.69 30.00 -15.00 15.00 [grid]
11 v=-0.016366: 4.73 2.41 31.16 -15.74 -34.09 -7.78 [rand]
12 v=-0.016230: -24.83 1.64 22.69 -30.00 -15.00 -15.00 [grid]
13 v=-0.016078: 8.00 4.97 -6.57 30.54 -19.59 20.03 [rand]
14 v=-0.016054: -15.57 -17.92 3.82 -4.32 22.85 -18.95 [rand]
15 v=-0.015962: 15.17 1.64 9.36 -15.00 -30.00 -30.00 [grid]
16 v=-0.015778: -41.28 -0.96 9.99 4.50 6.71 -7.94 [rand]
17 v=-0.015727: 15.64 7.17 23.76 -5.55 17.35 23.42 [rand]
18 v=-0.015637: 2.71 -2.24 0.86 -15.99 -13.53 -29.93 [rand]
19 v=-0.015555: 1.84 14.97 22.69 -15.00 -15.00 -15.00 [grid]
20 v=-0.015518: 4.65 -2.23 20.38 20.99 15.73 -16.09 [rand]
21 v=-0.015418: 8.29 -28.45 -21.65 2.96 2.59 18.65 [rand]
22 v=-0.015388: 1.84 -25.03 -17.31 15.00 -15.00 -15.00 [grid]
23 v=-0.015121: 15.17 -38.36 9.36 -30.00 30.00 -30.00 [grid]
24 v=-0.015068: -24.83 -38.36 9.36 -30.00 -30.00 -30.00 [grid]
25 v=-0.015019: 15.17 1.64 22.69 15.00 15.00 30.00 [grid]
26 v=-0.014990: 15.17 14.97 22.69 15.00 -30.00 -15.00 [grid]
27 v=-0.014860: -25.52 -27.42 10.69 24.25 -37.55 4.41 [rand]
28 v=-0.014852: 15.17 1.64 9.36 -30.00 30.00 15.00 [grid]
29 v=-0.014826: 15.17 -25.03 9.36 -30.00 30.00 -30.00 [grid]
30 v=-0.014823: 2.54 4.02 10.69 24.25 -37.55 -4.41 [rand]
31 v=-0.014815: -24.65 26.19 33.22 -14.03 -8.39 -25.20 [rand]
32 v=-0.014809: -24.83 14.97 -17.31 -30.00 -15.00 -30.00 [grid]
33 v=-0.014793: -24.83 1.64 9.36 -15.00 -30.00 -15.00 [grid]
34 v=-0.014759: -6.54 -22.88 19.26 -35.24 -13.60 -30.23 [rand]
35 v=-0.014755: 13.20 -16.31 12.41 -8.97 18.72 30.56 [rand]
36 v=-0.014729: 12.71 -22.04 0.55 -27.51 29.30 27.65 [rand]
37 v=-0.014702: 5.37 6.89 10.48 -19.57 -37.09 -16.59 [rand]
38 v=-0.014636: 15.17 1.64 22.69 -15.00 30.00 15.00 [grid]
39 v=-0.014634: -26.71 -48.13 -14.48 3.49 -11.25 -35.41 [rand]
40 v=-0.014625: -38.16 -25.03 -30.64 15.00 15.00 -15.00 [grid]
41 v=-0.014547: 1.84 14.97 22.69 -15.00 -15.00 30.00 [grid]
42 v=-0.014506: 1.84 1.64 9.36 15.00 -30.00 30.00 [grid]
43 v=-0.014465: -24.83 -38.36 9.36 15.00 30.00 -30.00 [grid]
44 v=-0.014458: 15.17 1.64 22.69 30.00 -30.00 15.00 [grid]
*[#8012=-0.0231938] *[#8014=-0.0235016] *[#8016=-0.0236742] *[#8017=-0.0239727] *[#8018=-0.0242408] *[#8020=-0.0248683] *[#8054=-0.0253632] *[#8056=-0.0261143] *[#8058=-0.0268665] *[#8339=-0.0269286] *[#8341=-0.0273273] *[#8342=-0.0273879] *[#8344=-0.0274693] *[#9374=-0.0275237] *[#9375=-0.0279147] *[#9380=-0.0284446] *[#9381=-0.0293261] *[#9382=-0.0295928] *[#9383=-0.0307181] *[#9385=-0.030963] *[#9386=-0.0311503] *[#9389=-0.0313224] *[#9391=-0.0314866] *[#9392=-0.0315236] + - costs of the above after a little optimization:
0 v=-0.024868: -23.92 1.04 8.93 15.07 -14.99 -29.54 [grid]
1 v=-0.026866: 2.90 -24.00 24.62 -14.78 15.05 30.77 [grid]
2 v=-0.021172: 7.66 -28.98 -1.11 29.83 -19.93 19.78 [rand]
3 v=-0.023299: 1.78 15.57 5.97 -32.23 13.32 28.63 [grid]
4 v=-0.019653: -16.38 -0.09 -27.04 -35.01 13.42 -30.49 [rand]
5 v=-0.025574: 8.95 16.08 30.85 1.99 -28.75 -14.59 [rand]
6 v=-0.025849: -6.75 -4.00 26.73 -43.99 -16.58 10.81 [rand]
7 v=-0.020187: 17.90 -39.85 29.88 7.57 27.65 26.99 [rand]
8 v=-0.018988: 1.33 14.82 -17.31 15.09 -10.69 -15.00 [grid]
9 v=-0.021262: 2.65 13.07 8.75 -15.08 28.30 -14.96 [grid]
10 v=-0.027469: 12.41 14.42 19.99 28.81 -18.37 10.68 [grid]
11 v=-0.019326: 2.27 1.78 30.99 -16.66 -33.67 -9.02 [rand]
12 v=-0.019453: -24.49 1.65 23.70 -30.13 -14.96 -14.61 [grid]
13 v=-0.018888: 7.58 4.17 -6.99 30.39 -20.59 19.99 [rand]
14 v=-0.022777: -16.47 -18.60 3.13 -3.89 26.64 -19.49 [rand]
15 v=-0.017029: 14.71 -2.32 9.41 -15.05 -29.51 -29.87 [grid]
16 v=-0.023860: -41.03 -0.27 11.58 4.58 6.35 -9.07 [rand]
17 v=-0.016762: 15.50 6.94 23.56 -5.54 17.36 23.66 [rand]
18 v=-0.019954: 2.79 2.20 1.10 -15.40 -13.40 -29.62 [rand]
19 v=-0.021719: 1.74 14.81 23.57 -12.08 -14.58 -13.91 [grid]
20 v=-0.017193: 5.08 -2.28 20.44 21.54 15.50 -15.41 [rand]
21 v=-0.016782: 8.31 -28.02 -21.65 3.45 2.57 19.10 [rand]
22 v=-0.019968: 2.36 -23.37 -16.60 15.34 -15.47 -15.08 [grid]
23 v=-0.019785: 16.57 -33.74 9.65 -29.13 30.22 -28.17 [grid]
24 v=-0.019569: -25.26 -37.85 7.23 -34.04 -30.60 -30.61 [grid]
25 v=-0.025539: 14.59 0.44 21.99 18.43 13.60 29.27 [grid]
26 v=-0.019970: 14.61 14.65 22.01 14.39 -25.66 -16.04 [grid]
27 v=-0.017985: -26.51 -27.74 10.43 24.43 -38.32 4.47 [rand]
28 v=-0.021026: 15.02 1.66 9.01 -29.85 29.56 19.32 [grid]
29 v=-0.018131: 15.13 -25.31 7.60 -30.54 28.70 -32.71 [grid]
30 v=-0.020603: 3.13 -1.39 10.58 24.89 -37.71 -3.50 [rand]
31 v=-0.015345: -24.64 26.48 33.24 -13.77 -8.13 -25.45 [rand]
32 v=-0.015142: -24.83 15.37 -17.30 -30.00 -15.00 -29.99 [grid]
33 v=-0.019544: -24.97 2.30 7.88 -15.68 -29.42 -14.58 [grid]
34 v=-0.026107: -5.78 -18.96 19.06 -34.83 -13.83 -31.39 [rand]
35 v=-0.021929: 15.14 -19.27 13.06 -9.76 22.97 31.13 [rand]
36 v=-0.022851: 17.16 -21.77 -0.07 -27.65 29.69 28.64 [rand]
37 v=-0.015690: 5.37 7.27 10.46 -19.58 -36.63 -16.60 [rand]
38 v=-0.021913: 18.37 3.37 20.20 -18.30 29.07 14.52 [grid]
39 v=-0.021658: -28.84 -48.79 -14.22 7.68 -11.70 -37.10 [rand]
40 v=-0.017059: -38.96 -25.39 -30.22 14.18 14.87 -14.79 [grid]
41 v=-0.026412: 2.13 18.12 23.13 -16.47 -16.13 30.90 [grid]
42 v=-0.020362: 1.17 2.47 10.66 18.15 -30.21 29.98 [grid]
43 v=-0.019816: -22.15 -38.31 9.11 14.26 30.18 -29.96 [grid]
*44 v=-0.031524: 15.51 9.76 26.68 34.72 -36.23 16.15 [grid]
+ - save #44 for twobest
+ - save #10 for twobest
+ - save # 1 for twobest
+ - save #41 for twobest
+ - save #34 for twobest
+ - save # 6 for twobest
+ - save # 5 for twobest
+ - save #25 for twobest
+ - save # 0 for twobest
+ - save #16 for twobest
+ - save # 3 for twobest
+ - save #36 for twobest
+ - save #14 for twobest
+ - save #35 for twobest
+ - save #38 for twobest
+ - save #19 for twobest
+ - save #39 for twobest
+ - save # 9 for twobest
+ - save # 2 for twobest
+ - save #28 for twobest
+ - save #30 for twobest
+ - save #42 for twobest
+ - Coarse startup search net CPU time = 0.0 s
++ Start refinement #1 on 12 coarse parameter sets
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.73
+ - Smoothing source; radius=1.73
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ 64586 total points stored in 736 'RHDD(7.60708)' bloks
+ - param set #1 has cost=-0.026479
+ -- Parameters = 16.2215 8.7457 26.3776 34.5054 -36.0299 16.7043 1.0155 1.0057 1.0049 0.0015 0.0034 0.0043
+ - param set #2 has cost=-0.022746
+ -- Parameters = 12.1852 15.0102 20.1542 29.4408 -18.2730 9.7535 1.0002 0.9999 1.0111 0.0004 -0.0019 0.0007
+ - param set #3 has cost=-0.026379
+ -- Parameters = 3.3124 -25.1277 24.8633 -14.8001 16.7320 31.5535 1.0007 1.0003 1.0030 0.0028 -0.0013 0.0013
+ - param set #4 has cost=-0.024786
+ -- Parameters = 2.2224 18.4242 23.8774 -16.2982 -16.9026 31.2338 0.9979 1.0173 0.9992 0.0000 -0.0009 0.0012
+ - param set #5 has cost=-0.024137
+ -- Parameters = -4.6498 -18.4775 19.0419 -34.6823 -14.2764 -31.0895 0.9899 0.9954 0.9999 0.0085 -0.0013 -0.0013
+ - param set #6 has cost=-0.024387
+ -- Parameters = -6.7519 -3.5739 26.8845 -43.3186 -16.8582 10.9768 1.0001 1.0002 0.9999 0.0016 -0.0003 0.0102
+ - param set #7 has cost=-0.022045
+ -- Parameters = 8.6976 16.0298 30.9245 2.0342 -28.4244 -14.7493 1.0000 0.9998 1.0000 0.0007 -0.0001 0.0008
+ - param set #8 has cost=-0.029658
+ -- Parameters = 14.4628 1.2380 20.5142 17.4061 12.8884 29.8108 1.0195 1.0072 1.0025 0.0040 -0.0027 0.0025
+ - param set #9 has cost=-0.023492
+ -- Parameters = -22.3215 -3.0161 9.2411 14.0489 -15.4619 -28.5935 0.9974 1.0075 1.0034 0.0021 0.0003 -0.0007
+ - param set #10 has cost=-0.015754
+ -- Parameters = -41.1503 -0.9794 12.0651 4.4159 6.2924 -9.3190 0.9993 1.0170 0.9989 -0.0010 -0.0011 -0.0001
+ - param set #11 has cost=-0.024567
+ -- Parameters = 2.1696 14.4887 5.8095 -32.2792 13.0661 27.7162 0.9997 0.9934 1.0022 0.0005 0.0015 0.0021
+ - param set #12 has cost=-0.020996
+ -- Parameters = -7.4202 -19.5787 -4.5353 -2.0793 1.1457 -0.4236 1.0020 1.0088 1.0131 -0.0072 -0.0001 0.0085
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ --- dist(#2,#1) = 0.544
+ --- dist(#3,#1) = 0.358
+ --- dist(#4,#1) = 0.374
+ --- dist(#5,#1) = 0.552
+ --- dist(#6,#1) = 0.675
+ --- dist(#7,#1) = 0.677
+ --- dist(#8,#1) = 0.649
+ --- dist(#9,#1) = 0.346
+ --- dist(#10,#1) = 0.495
+ --- dist(#11,#1) = 0.336
+ --- dist(#12,#1) = 0.695
++ Start refinement #2 on 12 coarse parameter sets
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.34
+ - Smoothing source; radius=1.34
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ 64353 total points stored in 748 'RHDD(7.52912)' bloks
+ - param set #1 has cost=-0.027788
+ -- Parameters = 14.0970 0.8611 20.7120 16.8405 12.7571 29.4767 1.0321 0.9980 1.0014 0.0070 -0.0014 0.0001
+ - param set #2 has cost=-0.023240
+ -- Parameters = 16.5967 8.3522 26.5036 34.0808 -36.0693 16.6212 1.0164 1.0054 1.0015 0.0012 0.0041 0.0045
+ - param set #3 has cost=-0.023370
+ -- Parameters = 3.7492 -25.8706 25.2041 -15.2226 16.5056 31.8804 0.9964 1.0035 0.9988 0.0104 -0.0072 -0.0018
+ - param set #4 has cost=-0.022504
+ -- Parameters = 2.1974 18.3549 24.2592 -16.5142 -17.1367 31.3686 1.0096 1.0161 1.0003 -0.0026 -0.0024 0.0024
+ - param set #5 has cost=-0.021890
+ -- Parameters = 2.3203 14.2823 5.8535 -32.1962 13.1184 27.6574 1.0007 0.9933 1.0032 0.0009 0.0017 0.0088
+ - param set #6 has cost=-0.023298
+ -- Parameters = -6.1952 -3.2403 26.6734 -42.8086 -17.8344 10.9566 1.0175 0.9985 1.0049 0.0006 -0.0018 0.0117
+ - param set #7 has cost=-0.020048
+ -- Parameters = -4.8366 -18.8258 18.6913 -34.4418 -14.2596 -31.3652 0.9887 0.9955 1.0006 0.0086 -0.0013 -0.0012
+ - param set #8 has cost=-0.020654
+ -- Parameters = -22.1182 -2.8413 9.1909 14.0488 -15.4422 -28.5306 0.9975 1.0173 1.0038 0.0023 0.0004 -0.0005
+ - param set #9 has cost=-0.022256
+ -- Parameters = 12.0172 15.0750 19.9304 29.3012 -18.1258 9.2558 1.0011 0.9924 1.0114 -0.0004 -0.0028 0.0024
+ - param set #10 has cost=-0.020049
+ -- Parameters = 8.1666 15.4000 31.2752 2.0698 -27.9150 -15.4678 1.0028 1.0240 0.9932 -0.0034 -0.0092 -0.0127
+ - param set #11 has cost=-0.022165
+ -- Parameters = -7.5335 -20.0728 -4.4943 -1.8965 1.5048 -3.0435 1.0033 1.0020 1.0148 -0.0073 0.0019 0.0092
+ - param set #12 has cost=-0.013957
+ -- Parameters = -40.8313 -0.8413 12.0765 4.8930 5.2536 -9.4364 0.9967 1.0269 0.9977 -0.0020 -0.0017 -0.0020
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ --- dist(#2,#1) = 0.356
+ --- dist(#3,#1) = 0.663
+ --- dist(#4,#1) = 0.543
+ --- dist(#5,#1) = 0.371
+ --- dist(#6,#1) = 0.343
+ --- dist(#7,#1) = 0.361
+ --- dist(#8,#1) = 0.545
+ --- dist(#9,#1) = 0.645
+ --- dist(#10,#1) = 0.499
+ --- dist(#11,#1) = 0.676
+ --- dist(#12,#1) = 0.687
++ Start refinement #3 on 12 coarse parameter sets
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.05
+ - Smoothing source; radius=1.05
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ - using 83035 points from base image [use_all=2]
+ * Exit alignment setup routine
+ 63291 total points stored in 742 'RHDD(7.48157)' bloks
+ - param set #1 has cost=-0.024336
+ -- Parameters = 14.1187 0.8828 20.7434 16.5813 12.8460 30.0161 1.0357 0.9983 1.0117 0.0054 -0.0068 -0.0081
+ - param set #2 has cost=-0.022973
+ -- Parameters = 4.4777 -25.9934 25.8420 -15.3839 16.3332 32.4821 1.0014 1.0062 0.9910 0.0057 -0.0089 -0.0112
+ - param set #3 has cost=-0.018197
+ -- Parameters = -5.7590 -3.3671 26.8432 -42.5681 -17.7782 11.3212 1.0256 0.9980 1.0053 0.0001 -0.0020 0.0117
+ - param set #4 has cost=-0.020662
+ -- Parameters = 16.4958 8.3483 26.4539 34.2508 -36.0745 16.6056 1.0161 0.9974 1.0024 0.0012 0.0044 0.0048
+ - param set #5 has cost=-0.018953
+ -- Parameters = 2.1706 18.4948 24.3577 -16.3990 -17.2723 31.3160 1.0099 1.0162 1.0001 0.0021 -0.0026 0.0026
+ - param set #6 has cost=-0.020637
+ -- Parameters = 11.9027 15.0777 19.8916 29.3447 -18.1611 9.1239 1.0000 0.9916 1.0096 -0.0009 -0.0035 0.0066
+ - param set #7 has cost=-0.024130
+ -- Parameters = -8.5786 -20.8752 -4.3985 -2.9652 2.0926 -3.3924 0.9729 1.0041 1.0088 -0.0167 0.0035 0.0109
+ - param set #8 has cost=-0.020442
+ -- Parameters = 1.7470 13.9685 5.7909 -32.2941 13.3299 27.6914 0.9874 0.9996 1.0080 0.0024 -0.0008 0.0108
+ - param set #9 has cost=-0.019524
+ -- Parameters = -22.0544 -3.0124 8.9268 14.7008 -15.5012 -28.4252 0.9918 1.0232 0.9959 0.0075 0.0135 0.0015
+ - param set #10 has cost=-0.018739
+ -- Parameters = 8.1731 15.1613 31.2958 2.1626 -27.7801 -15.7908 1.0028 1.0238 0.9930 -0.0030 -0.0040 -0.0125
+ - param set #11 has cost=-0.019804
+ -- Parameters = -4.9883 -18.8266 18.4915 -34.3060 -14.0771 -31.3249 0.9879 0.9953 1.0148 0.0091 0.0004 -0.0020
+ - param set #12 has cost=-0.013710
+ -- Parameters = -41.2379 -0.8433 11.9833 4.8082 5.9352 -9.4359 0.9936 1.0251 0.9917 -0.0126 -0.0009 -0.0075
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ --- dist(#2,#1) = 0.371
+ --- dist(#3,#1) = 0.355
+ --- dist(#4,#1) = 0.544
+ --- dist(#5,#1) = 0.345
+ --- dist(#6,#1) = 0.543
+ --- dist(#7,#1) = 0.682
+ --- dist(#8,#1) = 0.649
+ --- dist(#9,#1) = 0.366
+ --- dist(#10,#1) = 0.509
+ --- dist(#11,#1) = 0.657
+ --- dist(#12,#1) = 0.692
+ - Total coarse refinement net CPU time = 0.0 s; 2960 funcs
++ *** Fine pass begins ***
+ * Enter alignment setup routine
+ - Smoothing base; radius=1.00
+ - Smoothing source; radius=1.00
+ !source mask fill: ubot=0 usiz=77
+ - retaining old weight image
+ * Exit alignment setup routine
++ Picking best parameter set out of 13 cases
+ 63170 total points stored in 740 'RHDD(7.4754)' bloks
+ - cost(#1)=-0.023757 *
+ -- Parameters = 14.1187 0.8828 20.7434 16.5813 12.8460 30.0161 1.0357 0.9983 1.0117 0.0054 -0.0068 -0.0081
+ - cost(#2)=-0.023130
+ -- Parameters = -8.5786 -20.8752 -4.3985 -2.9652 2.0926 -3.3924 0.9729 1.0041 1.0088 -0.0167 0.0035 0.0109
+ - cost(#3)=-0.021934
+ -- Parameters = 4.4777 -25.9934 25.8420 -15.3839 16.3332 32.4821 1.0014 1.0062 0.9910 0.0057 -0.0089 -0.0112
+ - cost(#4)=-0.020620
+ -- Parameters = 16.4958 8.3483 26.4539 34.2508 -36.0745 16.6056 1.0161 0.9974 1.0024 0.0012 0.0044 0.0048
+ - cost(#5)=-0.020130
+ -- Parameters = 11.9027 15.0777 19.8916 29.3447 -18.1611 9.1239 1.0000 0.9916 1.0096 -0.0009 -0.0035 0.0066
+ - cost(#6)=-0.019893
+ -- Parameters = 1.7470 13.9685 5.7909 -32.2941 13.3299 27.6914 0.9874 0.9996 1.0080 0.0024 -0.0008 0.0108
+ - cost(#7)=-0.019779
+ -- Parameters = -4.9883 -18.8266 18.4915 -34.3060 -14.0771 -31.3249 0.9879 0.9953 1.0148 0.0091 0.0004 -0.0020
+ - cost(#8)=-0.019722
+ -- Parameters = -22.0544 -3.0124 8.9268 14.7008 -15.5012 -28.4252 0.9918 1.0232 0.9959 0.0075 0.0135 0.0015
+ - cost(#9)=-0.018865
+ -- Parameters = 2.1706 18.4948 24.3577 -16.3990 -17.2723 31.3160 1.0099 1.0162 1.0001 0.0021 -0.0026 0.0026
+ - cost(#10)=-0.019543
+ -- Parameters = 8.1731 15.1613 31.2958 2.1626 -27.7801 -15.7908 1.0028 1.0238 0.9930 -0.0030 -0.0040 -0.0125
+ - cost(#11)=-0.017782
+ -- Parameters = -5.7590 -3.3671 26.8432 -42.5681 -17.7782 11.3212 1.0256 0.9980 1.0053 0.0001 -0.0020 0.0117
+ - cost(#12)=-0.014161
+ -- Parameters = -41.2379 -0.8433 11.9833 4.8082 5.9352 -9.4359 0.9936 1.0251 0.9917 -0.0126 -0.0009 -0.0075
+ - cost(#13)=0.005226
+ -- Parameters = -11.4921 -11.6980 -3.9739 0.0000 0.0000 0.0000 1.0000 1.0000 1.0000 0.0000 0.0000 0.0000
+ -num_rtb 99 ==> refine all 13 cases
+ - cost(#1)=-0.024418 *
+ -- Parameters = 14.3779 0.8722 21.1826 16.3852 12.9293 30.2378 1.0375 0.9970 1.0026 0.0056 -0.0064 -0.0089
+ - cost(#2)=-0.024645 *
+ -- Parameters = -8.2545 -20.8388 -3.7363 -3.5421 2.3906 -3.1639 0.9712 0.9988 1.0080 -0.0192 0.0081 0.0109
+ - cost(#3)=-0.023247
+ -- Parameters = 4.5512 -25.6708 26.0902 -15.6811 16.3145 32.6327 1.0041 1.0207 0.9845 0.0053 -0.0099 -0.0085
+ - cost(#4)=-0.020928
+ -- Parameters = 16.6291 8.3561 26.4100 34.1161 -36.0983 16.5971 1.0141 0.9948 1.0041 -0.0007 0.0039 0.0051
+ - cost(#5)=-0.020272
+ -- Parameters = 11.8949 15.0997 19.9117 29.2718 -18.1548 9.0607 1.0019 0.9909 1.0086 -0.0005 -0.0037 0.0080
+ - cost(#6)=-0.021048
+ -- Parameters = 1.4116 13.4820 5.8495 -31.9231 13.7610 27.6395 0.9867 1.0015 1.0182 0.0032 -0.0007 0.0110
+ - cost(#7)=-0.020035
+ -- Parameters = -4.9471 -18.8311 18.3750 -34.2716 -14.1094 -31.2946 0.9884 0.9946 1.0191 0.0095 0.0002 -0.0026
+ - cost(#8)=-0.019934
+ -- Parameters = -22.1272 -3.1214 8.8960 14.7712 -15.4499 -28.5095 0.9919 1.0247 0.9972 0.0082 0.0134 -0.0009
+ - cost(#9)=-0.019515
+ -- Parameters = 2.1792 18.3929 24.5164 -16.2633 -17.2139 31.6223 1.0077 1.0185 1.0095 0.0026 -0.0022 0.0033
+ - cost(#10)=-0.019823
+ -- Parameters = 8.1269 15.0958 31.3265 2.1939 -27.7889 -15.8520 1.0033 1.0236 0.9935 -0.0027 -0.0007 -0.0123
+ - cost(#11)=-0.018110
+ -- Parameters = -5.5245 -3.4395 26.8576 -42.4438 -17.5436 11.5284 1.0273 0.9973 1.0063 0.0020 -0.0005 0.0109
+ - cost(#12)=-0.014392
+ -- Parameters = -41.2188 -0.8423 11.9957 4.6287 6.0137 -9.4365 0.9922 1.0254 0.9918 -0.0167 -0.0009 -0.0080
+ - cost(#13)=-0.030355 *
+ -- Parameters = -8.9538 -8.1442 -3.9384 1.4917 -3.2794 -6.4530 0.9953 0.9972 1.0017 0.0050 0.0052 0.0009
+ - case #13 is now the best
+ - Initial cost = -0.030355
+ - Initial fine Parameters = -8.9538 -8.1442 -3.9384 1.4917 -3.2794 -6.4530 0.9953 0.9972 1.0017 0.0050 0.0052 0.0009
+ - Finalish cost = -0.031012 ; 267 funcs
+ - Final cost = -0.031145 ; 184 funcs
+ Final fine fit Parameters:
x-shift=-8.8944 y-shift=-8.0605 z-shift=-4.2098
z-angle= 1.5925 x-angle=-3.4289 y-angle=-6.3804
x-scale= 0.9928 y-scale= 0.9913 z-scale= 1.0066
y/x-shear= 0.0083 z/x-shear=-0.0005 z/y-shear= 0.0011
+ - Fine net CPU time = 0.0 s
++ Computing output image
++ image warp: parameters = -8.8944 -8.0605 -4.2098 1.5925 -3.4289 -6.3804 0.9928 0.9913 1.0066 0.0083 -0.0005 0.0011
++ Output dataset ./__tt_aparc.a2009s+aseg_REN_all_ob_temp_al+orig.BRIK
++ Wrote -1Dmatrix_save ./aparc.a2009s+aseg_REN_all_al_e2a_only_mat.aff12.1D
++ 3dAllineate: total CPU time = 0.0 sec Elapsed = 38.9
++ ###########################################################
++ # Please check results visually for alignment quality #
++ ###########################################################
++ # '-autoweight' is recommended when using -lpc or -lpa #
++ # If your results are not good, please try again. #
++ ###########################################################
#Script is running (command trimmed):
cat_matvec -ONELINE ./aparc.a2009s+aseg_REN_all_al_e2a_only_mat.aff12.1D ./__tt_aparc.a2009s+aseg_REN_all_obla2e_mat.1D -I > ./aparc.a2009s+aseg_REN_all_al_mat.aff12.1D
#++ Combining anat to epi and oblique transformations
#Script is running (command trimmed):
3dAllineate -base ./__tt_dti_fa_color_ts_ns+orig -1Dmatrix_apply ./aparc.a2009s+aseg_REN_all_al_mat.aff12.1D -prefix ./aparc.a2009s+aseg_REN_all_al -input ./__tt_aparc.a2009s+aseg_REN_all+orig -master BASE -mast_dxyz 1.000000 -weight_frac 1.0 -maxrot 6 -maxshf 10 -VERB -warp aff -source_automask+4 -twobest 11 -twopass -VERB -maxrot 45 -maxshf 40 -fineblur 1 -source_automask+2
++ 3dAllineate: AFNI version=AFNI_17.1.09 (Jun 6 2017) [64-bit]
++ Authored by: Zhark the Registrator
*+ WARNING: If you are performing spatial transformations on an oblique dset,
such as ./__tt_dti_fa_color_ts_ns+orig.BRIK,
or viewing/combining it with volumes of differing obliquity,
you should consider running:
3dWarp -deoblique
on this and other oblique datasets in the same session.
See 3dWarp -help for details.
++ Oblique dataset:./__tt_dti_fa_color_ts_ns+orig.BRIK is 5.964928 degrees from plumb.
++ Source dataset: ./__tt_aparc.a2009s+aseg_REN_all+orig.HEAD
++ Base dataset: ./__tt_dti_fa_color_ts_ns+orig.HEAD
++ Loading datasets
+ Range param#4 [z-angle] = -6.000000 .. 6.000000
+ Range param#5 [x-angle] = -6.000000 .. 6.000000
+ Range param#6 [y-angle] = -6.000000 .. 6.000000
+ Range param#1 [x-shift] = -10.000000 .. 10.000000
+ Range param#2 [y-shift] = -10.000000 .. 10.000000
+ Range param#3 [z-shift] = -10.000000 .. 10.000000
+ Range param#4 [z-angle] = -45.000000 .. 45.000000
+ Range param#5 [x-angle] = -45.000000 .. 45.000000
+ Range param#6 [y-angle] = -45.000000 .. 45.000000
+ Range param#1 [x-shift] = -40.000000 .. 40.000000
+ Range param#2 [y-shift] = -40.000000 .. 40.000000
+ Range param#3 [z-shift] = -40.000000 .. 40.000000
++ changing output grid spacing to 1.0000 mm
++ OpenMP thread count = 15
++ ========== Applying transformation to 1 sub-bricks ==========
++ ========== sub-brick #0 ========== [total CPU to here=0.0 s]
+ * Enter alignment setup routine
+ - copying base image
+ - copying source image
+ - no weight image
+ - using 11 points from base image [use_all=0]
+ * Exit alignment setup routine
++ using -1Dmatrix_apply
++ Computing output image
++ image warp: parameters = 0.9804 -0.0128 0.1546 39.3888 0.1564 -0.0376 -0.9936 163.6616 0.0103 0.9909 -0.0384 36.1785
++ Output dataset ./aparc.a2009s+aseg_REN_all_al+orig.BRIK
++ 3dAllineate: total CPU time = 0.0 sec Elapsed = 0.7
++ ###########################################################
#++ Creating final output: anat data aligned to epi
# copy is not necessary
#++ Saving history
#Script is running (command trimmed):
3dNotes -h "align_epi_anat.py -anat aparc.a2009s+aseg_REN_all.nii.gz -epi \
dti_fa_color+orig -epi_base 0 -anat_has_skull no -epi_strip 3dAutomask \
-volreg off -tshift off -giant_move" \
./aparc.a2009s+aseg_REN_all_al+orig
#++ Removing all the temporary files
#Script is running:
\rm -f ./__tt_dti_fa_color*
#Script is running:
\rm -f ./__tt_aparc.a2009s+aseg_REN_all*
# Finished alignment successfully
| Subject | Author | Posted |
|---|---|---|
|
Flora699 | November 29, 2017 11:14PM |
|
Daniel Glen | November 30, 2017 01:35PM |
