Freesurfer

freesurfer@nmr.mgh.harvard.edu

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30085 discussions

Recon-all on 2 different DCM files
by Mattevada, Sravan 17 Nov '14

17 Nov '14

Hey Guys, I did a recon-all on 2 different dcm files the same subject. I posted the stats of the 2 recons below (blue and green). Can anyone please tell me if both the results are close enough to be considered as the same person? Thanks # Title Segmentation Statistics # Measure BrainSeg, BrainSegVol, Brain Segmentation Volume, 1147149.000000, mm^3 # Measure BrainSegNotVent, BrainSegVolNotVent, Brain Segmentation Volume Without Ventricles, 1106755.000000, mm^3 # Measure BrainSegNotVentSurf, BrainSegVolNotVentSurf, Brain Segmentation Volume Without Ventricles from Surf, 1105797.602179, mm^3 # Measure lhCortex, lhCortexVol, Left hemisphere cortical gray matter volume, 178265.204424, mm^3 # Measure rhCortex, rhCortexVol, Right hemisphere cortical gray matter volume, 178573.457404, mm^3 # Measure Cortex, CortexVol, Total cortical gray matter volume, 356838.661828, mm^3 # Measure lhCorticalWhiteMatter, lhCorticalWhiteMatterVol, Left hemisphere cortical white matter volume, 278821.965888, mm^3 # Measure rhCorticalWhiteMatter, rhCorticalWhiteMatterVol, Right hemisphere cortical white matter volume, 288297.974464, mm^3 # Measure CorticalWhiteMatter, CorticalWhiteMatterVol, Total cortical white matter volume, 567119.940351, mm^3 # Measure SubCortGray, SubCortGrayVol, Subcortical gray matter volume, 51897.000000, mm^3 # Measure TotalGray, TotalGrayVol, Total gray matter volume, 502065.661828, mm^3 # Measure SupraTentorial, SupraTentorialVol, Supratentorial volume, 1014280.602179, mm^3 # Measure SupraTentorialNotVent, SupraTentorialVolNotVent, Supratentorial volume, 979180.602179, mm^3 # Measure SupraTentorialNotVentVox, SupraTentorialVolNotVentVox, Supratentorial volume voxel count, 976438.000000, mm^3 # Measure Mask, MaskVol, Mask Volume, 1677160.000000, mm^3 # Measure BrainSegVol-to-eTIV, BrainSegVol-to-eTIV, Ratio of BrainSegVol to eTIV, 0.771851, unitless # Measure MaskVol-to-eTIV, MaskVol-to-eTIV, Ratio of MaskVol to eTIV, 1.128466, unitless # Measure lhSurfaceHoles, lhSurfaceHoles, Number of defect holes in lh surfaces prior to fixing, 81, unitless # Measure rhSurfaceHoles, rhSurfaceHoles, Number of defect holes in rh surfaces prior to fixing, 92, unitless # Measure SurfaceHoles, SurfaceHoles, Total number of defect holes in surfaces prior to fixing, 173, unitless # Measure EstimatedTotalIntraCranialVol, eTIV, Estimated Total Intracranial Volume, 1486230.461972, mm^3 # Excluding Cortical Gray and White Matter # ExcludeSegId 0 2 3 41 42 # VoxelVolume_mm3 1 # ColHeaders Index SegId NVoxels Volume_mm3 StructName normMean normStdDev normMin normMax normRange 1 4 12614 12613.8 Left-Lateral-Ventricle 51.1769 11.7938 28.0000 105.0000 77.0000 2 5 706 706.0 Left-Inf-Lat-Vent 60.9081 9.7501 30.0000 83.0000 53.0000 3 7 16205 16205.0 Left-Cerebellum-White-Matter 94.4526 5.0202 36.0000 107.0000 71.0000 4 8 46866 46866.0 Left-Cerebellum-Cortex 76.8904 9.8783 34.0000 117.0000 83.0000 5 10 7843 7843.2 Left-Thalamus-Proper 103.1140 8.5790 59.0000 121.0000 62.0000 6 11 2734 2734.4 Left-Caudate 90.8078 9.9212 61.0000 111.0000 50.0000 7 12 2748 2747.5 Left-Putamen 98.2484 5.0525 79.0000 112.0000 33.0000 8 13 1640 1640.1 Left-Pallidum 104.2372 3.9806 90.0000 115.0000 25.0000 9 14 2022 2022.4 3rd-Ventricle 57.2360 11.2028 33.0000 91.0000 58.0000 10 15 895 895.1 4th-Ventricle 53.9897 7.5234 29.0000 71.0000 42.0000 11 16 20089 20089.4 Brain-Stem 88.9277 11.8940 34.0000 113.0000 79.0000 12 17 4777 4777.2 Left-Hippocampus 83.7333 8.3881 53.0000 106.0000 53.0000 13 18 1245 1245.3 Left-Amygdala 86.5452 6.1434 59.0000 102.0000 43.0000 14 24 2417 2417.3 CSF 66.2343 11.6273 38.0000 105.0000 67.0000 15 26 202 201.7 Left-Accumbens-area 86.4204 6.8440 65.0000 99.0000 34.0000 16 28 4252 4252.3 Left-VentralDC 98.6040 11.8373 50.0000 120.0000 70.0000 17 30 0 0.0 Left-vessel 0.0000 0.0000 0.0000 0.0000 0.0000 18 31 1125 1125.3 Left-choroid-plexus 63.5452 11.2806 37.0000 96.0000 59.0000 19 43 19334 19334.1 Right-Lateral-Ventricle 47.7236 11.9759 26.0000 96.0000 70.0000 20 44 381 380.6 Right-Inf-Lat-Vent 59.5799 9.3492 31.0000 84.0000 53.0000 21 46 22199 22199.2 Right-Cerebellum-White-Matter 92.4601 4.8787 45.0000 109.0000 64.0000 22 47 44564 44564.1 Right-Cerebellum-Cortex 74.0031 9.9533 32.0000 105.0000 73.0000 23 49 6571 6571.4 Right-Thalamus-Proper 99.6773 9.6696 53.0000 116.0000 63.0000 24 50 2979 2978.8 Right-Caudate 84.3075 11.2002 54.0000 112.0000 58.0000 25 51 3272 3271.8 Right-Putamen 100.6600 4.7432 77.0000 114.0000 37.0000 26 52 1471 1470.7 Right-Pallidum 104.8643 3.8221 89.0000 117.0000 28.0000 27 53 4198 4198.0 Right-Hippocampus 84.3948 7.0679 53.0000 108.0000 55.0000 28 54 1463 1463.2 Right-Amygdala 84.8762 6.6090 56.0000 99.0000 43.0000 29 58 308 307.5 Right-Accumbens-area 93.4572 5.3543 78.0000 108.0000 30.0000 30 60 3574 3573.8 Right-VentralDC 95.2002 14.7423 39.0000 122.0000 83.0000 31 62 0 0.0 Right-vessel 0.0000 0.0000 0.0000 0.0000 0.0000 32 63 1380 1379.5 Right-choroid-plexus 62.8493 10.5738 35.0000 101.0000 66.0000 33 72 16 16.3 5th-Ventricle 63.4444 7.9204 49.0000 78.0000 29.0000 34 77 7309 7309.1 WM-hypointensities 79.9911 11.7723 40.0000 108.0000 68.0000 35 78 0 0.0 Left-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 36 79 0 0.0 Right-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 37 80 10 9.5 non-WM-hypointensities 71.1667 14.5404 53.0000 94.0000 41.0000 38 81 0 0.0 Left-non-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 39 82 0 0.0 Right-non-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 40 85 339 338.6 Optic-Chiasm 74.9807 16.3591 38.0000 109.0000 71.0000 41 251 832 832.5 CC_Posterior 105.5668 12.5924 67.0000 127.0000 60.0000 42 252 343 342.6 CC_Mid_Posterior 98.9137 10.3627 67.0000 117.0000 50.0000 43 253 267 266.6 CC_Central 104.3759 7.1576 80.0000 113.0000 33.0000 44 254 284 284.1 CC_Mid_Anterior 106.1203 7.2499 80.0000 116.0000 36.0000 45 255 511 511.1 CC_Anterior 106.4299 8.9098 67.0000 119.0000 52.0000 # Title Segmentation Statistics # Measure BrainSeg, BrainSegVol, Brain Segmentation Volume, 1141594.000000, mm^3 # Measure BrainSegNotVent, BrainSegVolNotVent, Brain Segmentation Volume Without Ventricles, 1101450.000000, mm^3 # Measure BrainSegNotVentSurf, BrainSegVolNotVentSurf, Brain Segmentation Volume Without Ventricles from Surf, 1100508.937477, mm^3 # Measure lhCortex, lhCortexVol, Left hemisphere cortical gray matter volume, 191427.646717, mm^3 # Measure rhCortex, rhCortexVol, Right hemisphere cortical gray matter volume, 193305.757680, mm^3 # Measure Cortex, CortexVol, Total cortical gray matter volume, 384733.404398, mm^3 # Measure lhCorticalWhiteMatter, lhCorticalWhiteMatterVol, Left hemisphere cortical white matter volume, 261874.458124, mm^3 # Measure rhCorticalWhiteMatter, rhCorticalWhiteMatterVol, Right hemisphere cortical white matter volume, 270384.074956, mm^3 # Measure CorticalWhiteMatter, CorticalWhiteMatterVol, Total cortical white matter volume, 532258.533079, mm^3 # Measure SubCortGray, SubCortGrayVol, Subcortical gray matter volume, 49354.000000, mm^3 # Measure TotalGray, TotalGrayVol, Total gray matter volume, 530741.404398, mm^3 # Measure SupraTentorial, SupraTentorialVol, Supratentorial volume, 1003805.937477, mm^3 # Measure SupraTentorialNotVent, SupraTentorialVolNotVent, Supratentorial volume, 969153.937477, mm^3 # Measure SupraTentorialNotVentVox, SupraTentorialVolNotVentVox, Supratentorial volume voxel count, 966844.000000, mm^3 # Measure Mask, MaskVol, Mask Volume, 1653467.000000, mm^3 # Measure BrainSegVol-to-eTIV, BrainSegVol-to-eTIV, Ratio of BrainSegVol to eTIV, 0.734385, unitless # Measure MaskVol-to-eTIV, MaskVol-to-eTIV, Ratio of MaskVol to eTIV, 1.063672, unitless # Measure lhSurfaceHoles, lhSurfaceHoles, Number of defect holes in lh surfaces prior to fixing, 137, unitless # Measure rhSurfaceHoles, rhSurfaceHoles, Number of defect holes in rh surfaces prior to fixing, 149, unitless # Measure SurfaceHoles, SurfaceHoles, Total number of defect holes in surfaces prior to fixing, 286, unitless # Measure EstimatedTotalIntraCranialVol, eTIV, Estimated Total Intracranial Volume, 1554489.673066, mm^3 # Excluding Cortical Gray and White Matter # ExcludeSegId 0 2 3 41 42 # VoxelVolume_mm3 1 # ColHeaders Index SegId NVoxels Volume_mm3 StructName normMean normStdDev normMin normMax normRange 1 4 11624 11623.6 Left-Lateral-Ventricle 50.4191 11.8898 26.0000 111.0000 85.0000 2 5 613 613.0 Left-Inf-Lat-Vent 62.7041 8.9657 36.0000 84.0000 48.0000 3 7 17895 17894.7 Left-Cerebellum-White-Matter 93.5453 5.7395 36.0000 176.0000 140.0000 4 8 46848 46847.7 Left-Cerebellum-Cortex 75.2992 10.4832 32.0000 137.0000 105.0000 5 10 7742 7741.9 Left-Thalamus-Proper 102.7636 9.1489 56.0000 122.0000 66.0000 6 11 2282 2281.5 Left-Caudate 98.5579 8.8743 69.0000 123.0000 54.0000 7 12 2832 2831.9 Left-Putamen 98.5576 6.2032 75.0000 114.0000 39.0000 8 13 1341 1341.1 Left-Pallidum 103.9716 5.0861 83.0000 116.0000 33.0000 9 14 2279 2279.2 3rd-Ventricle 49.9377 10.3587 30.0000 89.0000 59.0000 10 15 1058 1058.5 4th-Ventricle 53.5181 8.1795 31.0000 79.0000 48.0000 11 16 21113 21112.6 Brain-Stem 90.0067 11.5625 32.0000 126.0000 94.0000 12 17 4621 4620.9 Left-Hippocampus 85.4185 8.0210 51.0000 108.0000 57.0000 13 18 1288 1287.9 Left-Amygdala 89.0411 5.3142 68.0000 100.0000 32.0000 14 24 2181 2180.9 CSF 63.2374 11.2796 37.0000 103.0000 66.0000 15 26 285 284.5 Left-Accumbens-area 91.7901 6.2213 69.0000 107.0000 38.0000 16 28 4002 4002.0 Left-VentralDC 98.2775 11.9238 53.0000 120.0000 67.0000 17 30 0 0.0 Left-vessel 0.0000 0.0000 0.0000 0.0000 0.0000 18 31 1715 1715.5 Left-choroid-plexus 62.6751 11.3107 31.0000 100.0000 69.0000 19 43 19174 19173.7 Right-Lateral-Ventricle 46.8736 11.6110 27.0000 94.0000 67.0000 20 44 198 197.9 Right-Inf-Lat-Vent 61.6270 6.8874 46.0000 80.0000 34.0000 21 46 21541 21541.4 Right-Cerebellum-White-Matter 91.7927 5.0592 49.0000 107.0000 58.0000 22 47 48243 48243.4 Right-Cerebellum-Cortex 73.3856 10.2191 36.0000 98.0000 62.0000 23 49 6367 6366.8 Right-Thalamus-Proper 99.7574 9.0787 57.0000 118.0000 61.0000 24 50 2594 2594.4 Right-Caudate 85.5413 11.7252 49.0000 116.0000 67.0000 25 51 3463 3463.1 Right-Putamen 100.7573 5.6687 72.0000 116.0000 44.0000 26 52 761 760.5 Right-Pallidum 96.1806 7.6082 70.0000 115.0000 45.0000 27 53 4180 4180.0 Right-Hippocampus 85.4995 8.1312 53.0000 107.0000 54.0000 28 54 1205 1205.2 Right-Amygdala 86.3778 6.1255 61.0000 98.0000 37.0000 29 58 326 326.1 Right-Accumbens-area 92.3921 7.5403 70.0000 112.0000 42.0000 30 60 3659 3659.1 Right-VentralDC 92.1746 15.4662 35.0000 119.0000 84.0000 31 62 0 0.0 Right-vessel 0.0000 0.0000 0.0000 0.0000 0.0000 32 63 1941 1941.4 Right-choroid-plexus 62.5491 9.8952 36.0000 92.0000 56.0000 33 72 1 1.0 5th-Ventricle 79.0000 0.0000 79.0000 79.0000 0.0000 34 77 8877 8877.1 WM-hypointensities 79.8507 12.8359 32.0000 116.0000 84.0000 35 78 0 0.0 Left-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 36 79 0 0.0 Right-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 37 80 30 29.6 non-WM-hypointensities 70.0769 10.2837 50.0000 88.0000 38.0000 38 81 0 0.0 Left-non-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 39 82 0 0.0 Right-non-WM-hypointensities 0.0000 0.0000 0.0000 0.0000 0.0000 40 85 401 401.0 Optic-Chiasm 63.0072 9.7281 42.0000 91.0000 49.0000 41 251 309 308.9 CC_Posterior 103.6121 8.5291 77.0000 123.0000 46.0000 42 252 198 198.4 CC_Mid_Posterior 91.1027 6.3446 78.0000 105.0000 27.0000 43 253 264 263.9 CC_Central 90.3532 6.4921 72.0000 106.0000 34.0000 44 254 120 120.4 CC_Mid_Anterior 88.3944 6.8912 73.0000 108.0000 35.0000 45 255 179 178.7 CC_Anterior 93.0686 10.4366 74.0000 114.0000 40.0000 Sravan Mattevada, MSCS Computer Prog. Analyst III UNT Health Ph . 817 735 0499

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How is the actual thickness data stored?
by ye tian 17 Nov '14

17 Nov '14

Hello freesurfers, Suppose I do the following mris_preproc --fsgd gender_age.fsgd \ --cache-in thickness.fwhm10.fsaverage \ --target fsaverage --hemi lh \ --out lh.gender_age.thickness.10.mgh Then open the output file lh.gender_age.thickness.10.mgh in mathlab using result=MRIread('/path/rh.meditation.thickness.10.mgh'); Is it true that the actually thickness data is stored in result.volsize? Suppose that I have 27 subjects, is there a way to assign these numbers to their corresponding subjects? Thank you very much! Sincerely, Ye

2 1

temporal lobe exclusion
by O'Shea,Andrew 17 Nov '14

17 Nov '14

Hello all, I have heard about the issue of inaccuracy in the temporal lobes but never had problems myself until I recently tried processing a dataset from an outside group. On this data, the pial boundary are severely underestimated in the temporal lobes. It is worse right when the temporal lobes are coming into view as you slice back from the front of the brain along the coronal plane. I have attached a screenshot to show what I mean. Basically sections of the medial temporal lobe (greater than the hippocampus/amygdala area) and lateral temporal lobe are not included in the surfaces. The GM/WM contrast does not look very prominent in the t1 images. Is there any options we can specify which will lower the needed manual edits. I tried the ‘-mprage’ flag but that didn’t seem to help. Right now we have tried adding lots of control points but that doesn’t fix the issue 100%. Thanks for the help! -Andrew

2 1

prefrontal cortex label
by Anna Jonsson 17 Nov '14

17 Nov '14

Dear group, Is there a way to create a prefrontal cortex label in fresurfer? if so, please tell me the exact steps to do so, I am very confused. Thank you, Anna

3 5

Books
by Alex Spedding 17 Nov '14

17 Nov '14

Hi, Are there any books you could recommend that give an overview of some of the techniques Freesurfer uses? My research involves structural MRI so other books related to that would be good if you know any. I've got a couple of books on functional MRI analysis which I think are somewhat useful, as (I think) fMRI contain sMRI data though I could be completely wrong as I'm pretty new to this. Any book recommendations will be appreciated! Cheers, Alex

1 0

DICOM file selection for Recon-all
by Mattevada, Sravan 14 Nov '14

14 Nov '14

Hello Freesurfers, I am a beginner and have a question about the dicom file I need to select to do the recon-all process. I ran dcmunpack on the DICOM files I have with the following result Institution RADIOLOGY ASSOCIATES-CDI 1 LOCALIZER3PLANE 5 20 40 0.546875 ROW 180 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000000/IM000003 2 T1SESAG 8 345 90 0.8984375 ROW 140 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000001/IM000011 3 T2TSEAX 85 4170 180 0.8984375 ROW 110 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000002/IM000011 4 T1SEAX 8 410 90 0.8984375 ROW 140 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000003/IM000011 5 T2FLAIRAX 117 9000 180 0.8984375 ROW 130 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000004/IM000011 6 T2FL2DAXHEMO 27 855 20 0.8984375 ROW 80 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000005/IM000011 7 AXep2d_diff_2scan_trace 98 4100 90 1.796875\1.796875 COL 1260 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000006/IM000011 8 AXep2d_diff_2scan_trace_ADC 98 4100 90 1.796875\1.796875 COL 1260 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000007/IM000011 9 T2TSECOROBL 87 4260 180 0.4296875 ROW 110 /home/freesurfer/Desktop/9160/DICOM/PA000000/ST000000/SE000008/IM000011 I don't have one specific .dcm file to run the recon-all command The directory structure on the CD that I have has the 9 Folders (SE00000, SE000001 ...) Each folder has 6 - 25 files (IM00000, IM00000 ...) There are a total of 225 files When I use the software that came with the CD to see the images, I can see that each folder has series of images in different angles of the skull (different resolutions) Does recon-all use all the 225 images in all the folders? If yes how do I know which of the above dcmunpack results is the best option to start the recon-all process? I appreciate your help. Thanks Sravan Sravan Mattevada, MSCS Computer Prog. Analyst III UNT Health Ph . 817 735 0499

3 2

registration problem
by SHAHIN NASR 14 Nov '14

14 Nov '14

Hi, For one of my subjects, I have noticed a misalignment between sig.nii and orig.mgz when I try to show the sig map using either tkmedit (as below): cd /autofs/cluster/tootell/pitcairn/1/shahin/V2_Ori/Analysis tkmedit-sess -s ../Subjects/auil2 -a OriExp_TR3_1p5mm_PR -c ANG_90_45 or tkmedit-sess: cd /autofs/cluster/tootell/pitcairn/1/shahin/V2_Ori/Subjects tkmedit auil_anat orig.mgz -overlay auil2/bold/OriExp_TR3_1p5mm_PR/ANG_90_45/abs_sig.nii.gz -reg auil2/bold/register.dof6.dat~ I checked the registration file for this subjects and I don't see this problem there. tkregister2 --reg ../Subjects/auil2/bold/register.dof6.dat~ --mov ../Subjects/auil2/bold/template.nii.gz --surf I also checked the brain.mask and it covers the whole brain and looks fine to me. I also checked my other subjects and their results are fine. Do you have any idea why this is happening? P.S.: I process my data in in nmr-dev-env but I have also checked the above lines in nmr-stable53-env and problem is still there. -- Shahin Nasr PhD in Cognitive Neuroscience Martinos Imaging Center, MGH Harvard Medical School

2 1

Prefrontal white matter
by Alshikho, Mohamad J. 14 Nov '14

14 Nov '14

Hi Freesurfers, I want to calculate the FA in a VOI 8 mm3 in the left and right prefrontal white matter areas. My plan is to derive a mask for that area from aseg.mgz then I will register this mask to the FA map to calculate the FA value. Is it possible to derive like this mask from aseg.mgz and can I control the dimensions of that mask? thanks a lot Mohamad

3 7

Cortex/volume parcellation
by Octavian Lie 14 Nov '14

14 Nov '14

Dear all, Is there a way to generate random or seed-based whole cortical (surface) or brain (volumetric) parcellations in freesurfer or plugins, generating n equal area (volume) scouts, where the user can select the n? Thank you, Octavian

2 1

Freesurfer YouTube lecture slide download link 404
by Alex Spedding 14 Nov '14

14 Nov '14

Hi, Sorry if this is the wrong place to put this - never used a mailing list before - but I've been watching the FreeSurfer lectures on Youtube. The link to download the slides in the Introduction Lecture ( https://www.youtube.com/watch?v=GywOKtfKZIU ) the only one I've watched so far is broken. If you could fix the link that would be appreciated. Thank you, Alex Spedding

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