als, 4827 gradients
ignored
tol=1.0e-04, sigma=2.0, host=unkno, nav=16, nbrs=2, l_surf_repulse=1.000,
l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000
mom=0.00, dt=0.05
000: dt: 0., sse=21510736.0, rms=26.320
011: dt: 0.0500, sse=21370844.0, rms=26.231 (0.338%)
012: dt: 0.0500, sse=21233808.0, rms=26.144 (0.333%)
013: dt: 0.0500, sse=21098910.0, rms=26.057 (0.331%)
014: dt: 0.0500, sse=20965742.0, rms=25.972 (0.329%)
015: dt: 0.0500, sse=20834178.0, rms=25.887 (0.327%)
016: dt: 0.0500, sse=20703918.0, rms=25.802 (0.326%)
017: dt: 0.0500, sse=20575078.0, rms=25.719 (0.324%)
018: dt: 0.0500, sse=20447296.0, rms=25.635 (0.324%)
019: dt: 0.0500, sse=20320634.0, rms=25.553 (0.323%)
020: dt: 0.0500, sse=20195002.0, rms=25.470 (0.323%)
positioning took 1.1 minutes
mean border=46.3, 57994 (51335) missing vertices, mean dist 9.3 [0.1
(%0.0)->12.8 (%100.0))]
%24 local maxima, % 7 large gradients and %40 min vals, 4820 gradients
ignored
tol=1.0e-04, sigma=2.0, host=unkno, nav=16, nbrs=2, l_surf_repulse=1.000,
l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000
mom=0.00, dt=0.05
000: dt: 0., sse=20284860.0, rms=25.363
021: dt: 0.0500, sse=20159524.0, rms=25.281 (0.323%)
022: dt: 0.0500, sse=20035252.0, rms=25.199 (0.323%)
023: dt: 0.0500, sse=19911852.0, rms=25.118 (0.322%)
024: dt: 0.0500, sse=19789384.0, rms=25.037 (0.322%)
025: dt: 0.0500, sse=19667922.0, rms=24.957 (0.322%)
026: dt: 0.0500, sse=19547232.0, rms=24.877 (0.322%)
027: dt: 0.0500, sse=19427442.0, rms=24.797 (0.321%)
028: dt: 0.0500, sse=19308560.0, rms=24.717 (0.321%)
029: dt: 0.0500, sse=19190536.0, rms=24.638 (0.321%)
030: dt: 0.0500, sse=19073444.0, rms=24.559 (0.320%)
positioning took 1.2 minutes
mean border=46.3, 58182 (49681) missing vertices, mean dist 9.0 [0.1
(%0.1)->12.4 (%99.9))]
%24 local maxima, % 7 large gradients and %40 min vals, 4842 gradients
ignored
tol=1.0e-04, sigma=2.0, host=unkno, nav=16, nbrs=2, l_surf_repulse=5.000,
l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000
mom=0.00, dt=0.50
000: dt: 0., sse=19160218.0, rms=24.467
031: dt: 0.5000, sse=18407090.0, rms=23.957 (2.084%)
032: dt: 0.5000, sse=17688926.0, rms=23.460 (2.077%)
033: dt: 0.5000, sse=17006668.0, rms=22.976 (2.063%)
034: dt: 0.5000, sse=16360864.0, rms=22.507 (2.040%)
035: dt: 0.5000, sse=15751547.0, rms=22.055 (2.009%)
036: dt: 0.5000, sse=15177610.0, rms=21.620 (1.973%)
037: dt: 0.5000, sse=14637857.0, rms=21.201 (1.936%)
038: dt: 0.5000, sse=14127666.0, rms=20.797 (1.904%)
039: dt: 0.5000, sse=13644749.0, rms=20.407 (1.877%)
040: dt: 0.5000, sse=13185130.0, rms=20.028 (1.856%)
041: dt: 0.5000, sse=12746617.0, rms=19.660 (1.838%)
042: dt: 0.5000, sse=12325521.0, rms=19.300 (1.832%)
043: dt: 0.5000, sse=11921329.0, rms=18.948 (1.825%)
044: dt: 0.5000, sse=11532627.0, rms=18.603 (1.819%)
045: dt: 0.5000, sse=11158549.0, rms=18.265 (1.816%)
046: dt: 0.5000, sse=10795637.0, rms=17.932 (1.826%)
047: dt: 0.5000, sse=10442737.0, rms=17.601 (1.845%)
048: dt: 0.5000, sse=10097535.0, rms=17.271 (1.871%)
049: dt: 0.5000, sse=9762229.0, rms=16.945 (1.887%)
050: dt: 0.5000, sse=9437930.0, rms=16.624 (1.896%)
051: dt: 0.5000, sse=9120953.0, rms=16.304 (1.927%)
052: dt: 0.5000, sse=8813598.0, rms=15.987 (1.940%)
053: dt: 0.5000, sse=8514504.0, rms=15.673 (1.965%)
054: dt: 0.5000, sse=8222812.0, rms=15.361 (1.991%)
055: dt: 0.5000, sse=7938257.0, rms=15.051 (2.021%)
056: dt: 0.5000, sse=7662795.0, rms=14.744 (2.040%)
Segmentation fault (core dumped)
Data were here:
https://pitt.box.com/s/6269a9mnwbs6zi0azn08dn55u47yfa7i
Douglas N. Greve
<https://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=from:%22Douglas+N.+Greve%22>
Mon, 24 Feb 2020 06:34:51 -0800
<https://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=date:20200224>
Try setting -max XXX
where XXX is the maximum allowable thickness. It is default to 5, so
try something
large
On 2/21/2020 11:36 AM, CiRong Liu wrote:
External Email - Use Caution
Dear experts of the freesurfer,
I was trying to create the white matter and pial surfaces of the cerebellum
of the marmoset, based on ultra-high (80um) resolution ex-vivo images.
I manually segment the cerebellum into the white matter and the gray matter
and change the header information to 1mm.
Based on the manual segmented files, I created white matter surfaces
(rh.orig).
I tried to use the mris_make_surfaces to expand the white matter to create
the matched pial surface.
However, the /mris_make_surfaces/ failed to push the surface enough. See
the attached files and screenshots.
I tried smoothing the segmentation, enhancing the contrasts, and tested
different expert option (for example: -max_csf 0.1 -min_gray_at_csf_border
1)
This was this best I got, but still cannot get an optimal result (not pushed
enough):
/mris_mask_surfaces -max_csf 0.1 -min_gray_
