defacing issue crop image #27
Comments
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Can you provide an MWE https://stackoverflow.com/help/minimal-reproducible-example ? Also, you can either find the mask by looking at voxels that are different from the non-masked image or you can dig into the temporary files (currently) that are generated https://github.com/poldracklab/pydeface/blob/master/pydeface/utils.py#L116. You can then cut the mask to where it needs to stop (aka the neck). |
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Looking a bit more I'd recommend setting |
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@muschellij2 I followed your advice and I saved the mask. The mask doesn't include the complete VOI. Do I have to manually modify the mask to include the complete neck region or is there a parameter that I could change to expand the coverage? |
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Again, almost impossible to diagnose without an MWE https://stackoverflow.com/help/minimal-reproducible-example ? |
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Is this what you're looking for? This relies on my implementation of library(RNifti)
library(fslr)
#> Loading required package: oro.nifti
#> oro.nifti 0.10.1
#>
#> Attaching package: 'oro.nifti'
#> The following object is masked from 'package:RNifti':
#>
#> origin
#> Loading required package: neurobase
fname = "sub-chiba750_anat_sub-chiba750_T1w.nii.gz"
download.file(url = paste0("https://openneuro.org/crn/datasets/ds002393/",
"snapshots/1.0.2/files/",
"sub-chiba750:anat:sub-chiba750_T1w.nii.gz"),
destfile = fname)
img = RNifti::readNifti(fname)
out = face_removal_mask(fname)
#> Warning in get.fsl(): Setting fsl.path to /usr/local/fsl
#> Warning in get.fsloutput(): Can't find FSLOUTPUTTYPE, setting to NIFTI_GZ
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/flirt -in "/usr/local/fsl/data/standard/MNI152_T1_1mm.nii.gz" -ref "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpK4U4ug/reprex17ffa74bf4484/sub-chiba750_anat_sub-chiba750_T1w.nii.gz" -out "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpKjcGt4/file58d7925ddcf" -dof 12 -omat "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpKjcGt4/file58d19f2c8d.mat" -cost mutualinfo
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/flirt -in "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpKjcGt4/file58dbe034b1.nii.gz" -ref "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpK4U4ug/reprex17ffa74bf4484/sub-chiba750_anat_sub-chiba750_T1w.nii.gz" -applyxfm -init "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpKjcGt4/file58d19f2c8d.mat" -interp nearestneighbour -out "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpKjcGt4/file58d25057f2c"
out_img = readnii(out)
ortho2(img)Here is my extension. The idea is to find all the indices in x, y, and z-planes that are in the mask. We then extend down in the z-plane ( xx = which(out_img == 0, arr.ind = TRUE)
dim3 = 1:(min(xx[,3]) + floor( (max(xx[,3]) - min(xx[,3]))/2))
dim2 = min(xx[,2]):dim(out_img)[2]
# eg = expand.grid(dim1 = unique(xx[,1]),
# dim2 = unique(xx[,2]), dim3 = dim3)
eg = expand.grid(dim1 = unique(xx[,1]),
dim2 = dim2, dim3 = dim3)
eg = as.matrix(eg)
new_mask = out_img
new_mask[eg] = 0
final_img = img * new_mask
ortho2(final_img)Created on 2020-01-23 by the reprex package (v0.3.0.9001) Session infosessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 3.6.0 (2019-04-26)
#> os macOS Mojave 10.14.6
#> system x86_64, darwin15.6.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/New_York
#> date 2020-01-23
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib source
#> abind 1.4-5 2016-07-21 [1] CRAN (R 3.6.0)
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0)
#> backports 1.1.5 2019-10-02 [1] CRAN (R 3.6.0)
#> bitops 1.0-6 2013-08-17 [1] CRAN (R 3.6.0)
#> cli 2.0.1 2020-01-08 [1] CRAN (R 3.6.0)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0)
#> curl 4.3 2019-12-02 [1] CRAN (R 3.6.0)
#> digest 0.6.23 2019-11-23 [1] CRAN (R 3.6.0)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 3.6.0)
#> fansi 0.4.1 2020-01-08 [1] CRAN (R 3.6.0)
#> fs 1.3.1 2019-05-06 [1] CRAN (R 3.6.0)
#> fslr * 2.24.4 2019-12-03 [1] local
#> glue 1.3.1 2019-03-12 [1] CRAN (R 3.6.0)
#> highr 0.8 2019-03-20 [1] CRAN (R 3.6.0)
#> htmltools 0.4.0 2019-10-04 [1] CRAN (R 3.6.0)
#> httr 1.4.1 2019-08-05 [1] CRAN (R 3.6.0)
#> knitr 1.26.1 2020-01-05 [1] Github (muschellij2/knitr@f5af631)
#> magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
#> matrixStats 0.55.0 2019-09-07 [1] CRAN (R 3.6.0)
#> mime 0.8 2019-12-19 [1] CRAN (R 3.6.0)
#> neurobase * 1.29.1 2020-01-14 [1] local
#> oro.nifti * 0.10.1 2019-12-14 [1] local
#> pillar 1.4.3 2019-12-20 [1] CRAN (R 3.6.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 3.6.0)
#> purrr 0.3.3 2019-10-18 [1] CRAN (R 3.6.0)
#> R.methodsS3 1.7.1 2016-02-16 [1] CRAN (R 3.6.0)
#> R.oo 1.23.0 2019-11-03 [1] CRAN (R 3.6.0)
#> R.utils 2.9.0 2019-06-13 [1] CRAN (R 3.6.0)
#> R6 2.4.1 2019-11-12 [1] CRAN (R 3.6.0)
#> Rcpp 1.0.3 2019-11-08 [1] CRAN (R 3.6.0)
#> reprex 0.3.0.9001 2020-01-05 [1] Github (tidyverse/reprex@5ae0b29)
#> rlang 0.4.2 2019-11-23 [1] CRAN (R 3.6.0)
#> rmarkdown 2.0.7 2020-01-17 [1] Github (rstudio/rmarkdown@2faf16a)
#> RNifti * 1.0.1 2019-11-27 [1] CRAN (R 3.6.0)
#> rstudioapi 0.10.0-9003 2020-01-05 [1] Github (rstudio/rstudioapi@abe596d)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0)
#> stringi 1.4.5 2020-01-11 [1] CRAN (R 3.6.0)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0)
#> styler 1.1.1 2019-05-06 [1] CRAN (R 3.6.0)
#> tibble 2.1.3 2019-06-06 [1] CRAN (R 3.6.0)
#> withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0)
#> xfun 0.11 2019-11-12 [1] CRAN (R 3.6.0)
#> xml2 1.2.2 2019-08-09 [1] CRAN (R 3.6.0)
#> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.6.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library |
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This may be more clear as to what is getting added. library(RNifti)
library(fslr)
#> Loading required package: oro.nifti
#> oro.nifti 0.10.1
#>
#> Attaching package: 'oro.nifti'
#> The following object is masked from 'package:RNifti':
#>
#> origin
#> Loading required package: neurobase
fname = "sub-chiba750_anat_sub-chiba750_T1w.nii.gz"
download.file(url = paste0("https://openneuro.org/crn/datasets/ds002393/",
"snapshots/1.0.2/files/",
"sub-chiba750:anat:sub-chiba750_T1w.nii.gz"),
destfile = fname)
img = RNifti::readNifti(fname)
out = face_removal_mask(fname)
#> Warning in get.fsl(): Setting fsl.path to /usr/local/fsl
#> Warning in get.fsloutput(): Can't find FSLOUTPUTTYPE, setting to NIFTI_GZ
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/flirt -in "/usr/local/fsl/data/standard/MNI152_T1_1mm.nii.gz" -ref "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpK4U4ug/reprex17ffa365ce2a8/sub-chiba750_anat_sub-chiba750_T1w.nii.gz" -out "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpwhfPxR/file5f0382ef3d6" -dof 12 -omat "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpwhfPxR/file5f042b7e932.mat" -cost mutualinfo
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/flirt -in "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpwhfPxR/file5f043b9ef4f.nii.gz" -ref "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpK4U4ug/reprex17ffa365ce2a8/sub-chiba750_anat_sub-chiba750_T1w.nii.gz" -applyxfm -init "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpwhfPxR/file5f042b7e932.mat" -interp nearestneighbour -out "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpwhfPxR/file5f0128a836b"
out_img = readnii(out)
ortho2(img)ortho2(img, out_img)xx = which(out_img == 0, arr.ind = TRUE)
dim3 = 1:(min(xx[,3]) + floor( (max(xx[,3]) - min(xx[,3]))/2))
dim2 = min(xx[,2]):dim(out_img)[2]
# eg = expand.grid(dim1 = unique(xx[,1]),
# dim2 = unique(xx[,2]), dim3 = dim3)
eg = expand.grid(dim1 = unique(xx[,1]),
dim2 = dim2, dim3 = dim3)
eg = as.matrix(eg)
new_mask = out_img
new_mask[eg] = 0
final_img = img * new_mask
ortho2(final_img)ortho2(img, new_mask == 0)Created on 2020-01-23 by the reprex package (v0.3.0.9001) Session infosessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 3.6.0 (2019-04-26)
#> os macOS Mojave 10.14.6
#> system x86_64, darwin15.6.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/New_York
#> date 2020-01-23
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib source
#> abind 1.4-5 2016-07-21 [1] CRAN (R 3.6.0)
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0)
#> backports 1.1.5 2019-10-02 [1] CRAN (R 3.6.0)
#> bitops 1.0-6 2013-08-17 [1] CRAN (R 3.6.0)
#> cli 2.0.1 2020-01-08 [1] CRAN (R 3.6.0)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0)
#> curl 4.3 2019-12-02 [1] CRAN (R 3.6.0)
#> digest 0.6.23 2019-11-23 [1] CRAN (R 3.6.0)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 3.6.0)
#> fansi 0.4.1 2020-01-08 [1] CRAN (R 3.6.0)
#> fs 1.3.1 2019-05-06 [1] CRAN (R 3.6.0)
#> fslr * 2.24.4 2019-12-03 [1] local
#> glue 1.3.1 2019-03-12 [1] CRAN (R 3.6.0)
#> highr 0.8 2019-03-20 [1] CRAN (R 3.6.0)
#> htmltools 0.4.0 2019-10-04 [1] CRAN (R 3.6.0)
#> httr 1.4.1 2019-08-05 [1] CRAN (R 3.6.0)
#> knitr 1.26.1 2020-01-05 [1] Github (muschellij2/knitr@f5af631)
#> magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
#> matrixStats 0.55.0 2019-09-07 [1] CRAN (R 3.6.0)
#> mime 0.8 2019-12-19 [1] CRAN (R 3.6.0)
#> neurobase * 1.29.1 2020-01-14 [1] local
#> oro.nifti * 0.10.1 2019-12-14 [1] local
#> pillar 1.4.3 2019-12-20 [1] CRAN (R 3.6.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 3.6.0)
#> purrr 0.3.3 2019-10-18 [1] CRAN (R 3.6.0)
#> R.methodsS3 1.7.1 2016-02-16 [1] CRAN (R 3.6.0)
#> R.oo 1.23.0 2019-11-03 [1] CRAN (R 3.6.0)
#> R.utils 2.9.0 2019-06-13 [1] CRAN (R 3.6.0)
#> R6 2.4.1 2019-11-12 [1] CRAN (R 3.6.0)
#> Rcpp 1.0.3 2019-11-08 [1] CRAN (R 3.6.0)
#> reprex 0.3.0.9001 2020-01-05 [1] Github (tidyverse/reprex@5ae0b29)
#> rlang 0.4.2 2019-11-23 [1] CRAN (R 3.6.0)
#> rmarkdown 2.0.7 2020-01-17 [1] Github (rstudio/rmarkdown@2faf16a)
#> RNifti * 1.0.1 2019-11-27 [1] CRAN (R 3.6.0)
#> rstudioapi 0.10.0-9003 2020-01-05 [1] Github (rstudio/rstudioapi@abe596d)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0)
#> stringi 1.4.5 2020-01-11 [1] CRAN (R 3.6.0)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0)
#> styler 1.1.1 2019-05-06 [1] CRAN (R 3.6.0)
#> tibble 2.1.3 2019-06-06 [1] CRAN (R 3.6.0)
#> withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0)
#> xfun 0.11 2019-11-12 [1] CRAN (R 3.6.0)
#> xml2 1.2.2 2019-08-09 [1] CRAN (R 3.6.0)
#> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.6.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library |
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@muschellij2 Thanks for your help. I tried to follow the instructions above, but I ran into trouble . I noticed that I have a different version of fslr & oro.nifti than you. |
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Yeah, I'm trying to update the packages on my end, I thikn oyu need to install: remotes::install_github("muschellij2/oro.nifti") |
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Thanks. I managed to reproduce the results for the give case. I'll try to create a script to do a batch processing for the complete dataset. |
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@muschellij2 I tried to run the script for T2w, but I ran into some issues. |
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So the overall process works on the fact you can register a brain to a
brain, or really a head to a head. That image you are downloading really
isn't a brain/head, but more like half a brain a lot of the spinal cord.
Not only that, the image is very narrow and not a full head/next. The
affine transformation won't handle this well and you need to use a
different approach.
Best,
John
…On Wed, Feb 12, 2020 at 11:56 AM alexfoias ***@***.***> wrote:
@muschellij2 <https://github.com/muschellij2> I tried to run the script
for T2w, but I ran into some issues.
Here is the output:
https://gist.github.com/alexfoias/53b5a3b80502737edabb68e8e33d44b9
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Also, someone from @poldrack @poldracklab probably should weigh in. |
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Agree with @muschellij2 's previous comment. Defacing does not work by default because your coverage is not a conventional brain image. I would recommend using Here (Note: I am not from @poldrack 's lab, but I put these extra flags to the command line interface to cover for such use cases.) |
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@alexfoias with regards to T2w image defacing, see the |
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You can make some adaptations, but you really need to see the above comments, but here's something that works for this one file (need to extend mask): library(RNifti)
library(fslr)
#> Loading required package: oro.nifti
#> oro.nifti 0.10.2
#>
#> Attaching package: 'oro.nifti'
#> The following object is masked from 'package:RNifti':
#>
#> origin
#> Loading required package: neurobase
library(extrantsr)
#>
#> Attaching package: 'extrantsr'
#> The following object is masked from 'package:neurobase':
#>
#> zero_pad
#> The following objects are masked from 'package:oro.nifti':
#>
#> origin, origin<-
#> The following object is masked from 'package:RNifti':
#>
#> origin
fname = file.path(tempdir(),
"sub-chibaIngeniasub-chibaIngenia_T2w.nii.gz")
if (!file.exists(fname)) {
download.file(url = paste0(
"https://openneuro.org/crn/datasets/ds002393/",
"snapshots/1.0.2/files/",
"sub-chibaIngenia:anat:sub-chibaIngenia_T2w.nii.gz"),
destfile = fname)
}
img = RNifti::readNifti(fname)
tfname = mni_fname(mm = "1")
#> Warning in get.fsl(): Setting fsl.path to /usr/local/fsl
#> Warning in get.fsloutput(): Can't find FSLOUTPUTTYPE, setting to NIFTI_GZ
face_fname = mni_face_fname(mm = "1")
face = readnii(face_fname)
timg = readnii(tfname)
timg = copyNIfTIHeader(timg, timg[(91-30):(91+30), , 1:70])
face = copyNIfTIHeader(face, face[(91-30):(91+30), , 1:70])
noneck <- double_remove_neck(
fname,
template.file = file.path(fsldir(),
"data/standard", "MNI152_T1_1mm_brain.nii.gz"),
template.mask = file.path(fsldir(),
"data/standard", "MNI152_T1_1mm_brain_mask.nii.gz"))
#> # Registration to template
#> # Swapping Dimensions
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslhd "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/sub-chibaIngeniasub-chibaIngenia_T2w.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslorient -getorient "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/sub-chibaIngeniasub-chibaIngenia_T2w.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslorient -swaporient "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa35f6f8ac/sub-chibaIngeniasub-chibaIngenia_T2w.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslswapdim "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa35f6f8ac/sub-chibaIngeniasub-chibaIngenia_T2w.nii.gz" RL PA IS "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa693fffe1";
#> # Running Registration of file to template
#> # Applying Registration output is
#> $warpedmovout
#> antsImage
#> Pixel Type : float
#> Components Per Pixel: 1
#> Dimensions : 63x320x320
#> Voxel Spacing : 0.799999237060547x0.800000011920929x0.800000011920929
#> Origin : -13.47086 120.9473 -144.1494
#> Direction : 0.9991751 -0.02116131 0.03466073 -0.02100112 -0.9997671 -0.004979392 -0.03475802 -0.00424737 0.9993867
#>
#>
#> $warpedfixout
#> antsImage
#> Pixel Type : float
#> Components Per Pixel: 1
#> Dimensions : 182x218x182
#> Voxel Spacing : 1x1x1
#> Origin : -90 126 -72
#> Direction : 1 0 0 0 -1 0 0 0 1
#>
#>
#> $fwdtransforms
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa192704440GenericAffine.mat"
#>
#> $invtransforms
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa192704440GenericAffine.mat"
#>
#> $prev_transforms
#> character(0)
#> # Applying Transformations to file
#> # Applying Transforms to other.files
#> # Writing out file
#> # Writing out other.files
#> # Removing Warping images
#> # Reading data back into R
#> # Reading in Transformed data
#> # Dropping slices not in mask
#> # Swapping Dimensions Back
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslorient -swaporient "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa6c3724a6.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslswapdim "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa6c3724a6.nii.gz" LR PA IS "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa184745cb";
#> # Registration to template
#> # Swapping Dimensions
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslhd "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa6f371ee0.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslorient -getorient "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa6f371ee0.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslorient -swaporient "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaadc3d81a/file6aaa6f371ee0.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslswapdim "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaadc3d81a/file6aaa6f371ee0.nii.gz" RL PA IS "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa34a09a05";
#> # Running Registration of file to template
#> # Applying Registration output is
#> $warpedmovout
#> antsImage
#> Pixel Type : float
#> Components Per Pixel: 1
#> Dimensions : 63x320x320
#> Voxel Spacing : 0.799999237060547x0.800000011920929x0.800000011920929
#> Origin : -13.47086 120.9473 -144.1494
#> Direction : 0.9991751 -0.02116131 0.03466073 -0.02100112 -0.9997671 -0.004979392 -0.03475802 -0.00424737 0.9993867
#>
#>
#> $warpedfixout
#> antsImage
#> Pixel Type : float
#> Components Per Pixel: 1
#> Dimensions : 182x218x182
#> Voxel Spacing : 1x1x1
#> Origin : -90 126 -72
#> Direction : 1 0 0 0 -1 0 0 0 1
#>
#>
#> $fwdtransforms
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa53048b30GenericAffine.mat"
#>
#> $invtransforms
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa53048b30GenericAffine.mat"
#>
#> $prev_transforms
#> character(0)
#> # Applying Transformations to file
#> # Applying Transforms to other.files
#> # Writing out file
#> # Writing out other.files
#> # Removing Warping images
#> # Reading data back into R
#> # Reading in Transformed data
#> # Dropping slices not in mask
#> # Swapping Dimensions Back
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslorient -swaporient "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa14448914.nii.gz"
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslswapdim "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmppwGYy3/file6aaa14448914.nii.gz" LR PA IS "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa1f838a71";
reg = registration(
filename = timg,
template.file = noneck,
typeofTransform = "Rigid")
#> # Running Registration of file to template
#> # Applying Registration output is
#> $fwdtransforms
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa46ce1e1d0GenericAffine.mat"
#>
#> $invtransforms
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa46ce1e1d0GenericAffine.mat"
#>
#> $prev_transforms
#> character(0)
#> # Applying Transformations to file
#> [1] "-d"
#> [2] "3"
#> [3] "-i"
#> [4] "<pointer: 0x7f80bf75cd20>"
#> [5] "-o"
#> [6] "<pointer: 0x7f80c6168d60>"
#> [7] "-r"
#> [8] "<pointer: 0x7f80bf79e8f0>"
#> [9] "-n"
#> [10] "linear"
#> [11] "-t"
#> [12] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa46ce1e1d0GenericAffine.mat"
#> # Writing out file
#> [1] "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmppwGYy3/file6aaa74f610e0.nii.gz"
#> # Reading data back into R
out_img = ants_apply_transforms(moving = 1 - face,
fixed = noneck,
transformlist = reg$fwdtransforms,
interpolator = "nearestNeighbor")
ortho2(img, out_img)xx = which(out_img == 1, arr.ind = TRUE)
dim3 = 1:(min(xx[,3]) + floor( (max(xx[,3]) - min(xx[,3]))/2))
dim2 = min(xx[,2]):dim(out_img)[2]
# eg = expand.grid(dim1 = unique(xx[,1]),
# dim2 = unique(xx[,2]), dim3 = dim3)
eg = expand.grid(dim1 = unique(xx[,1]),
dim2 = dim2, dim3 = dim3)
eg = as.matrix(eg)
new_mask = out_img
new_mask[eg] = 1
ortho2(img, new_mask)ortho2(img, 1 - new_mask)Created on 2020-02-12 by the reprex package (v0.3.0.9001) Session infosessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 3.6.2 (2019-12-12)
#> os macOS Mojave 10.14.6
#> system x86_64, darwin15.6.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/New_York
#> date 2020-02-12
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib source
#> abind 1.4-5 2016-07-21 [1] CRAN (R 3.6.0)
#> ANTsR 0.5.4.2 2019-12-06 [1] Neuroconductor-Releases (R 3.6.1)
#> ANTsRCore 0.7.3 2019-12-05 [1] Neuroconductor-Releases (R 3.6.1)
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0)
#> backports 1.1.5 2019-10-02 [1] CRAN (R 3.6.0)
#> bitops 1.0-6 2013-08-17 [1] CRAN (R 3.6.0)
#> cli 2.0.1 2020-01-08 [1] CRAN (R 3.6.0)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0)
#> curl 4.3 2019-12-02 [1] CRAN (R 3.6.0)
#> digest 0.6.23 2019-11-23 [1] CRAN (R 3.6.0)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 3.6.0)
#> extrantsr * 3.9.12.1 2020-01-03 [1] local
#> fansi 0.4.1 2020-01-08 [1] CRAN (R 3.6.0)
#> fs 1.3.1 2019-05-06 [1] CRAN (R 3.6.0)
#> fslr * 2.24.4 2020-02-12 [1] local
#> glue 1.3.1 2019-03-12 [1] CRAN (R 3.6.0)
#> highr 0.8 2019-03-20 [1] CRAN (R 3.6.0)
#> htmltools 0.4.0 2019-10-04 [1] CRAN (R 3.6.0)
#> httr 1.4.1 2019-08-05 [1] CRAN (R 3.6.0)
#> ITKR 0.5.2 2019-11-28 [1] Neuroconductor-Releases (R 3.6.1)
#> knitr 1.26.1 2020-01-05 [1] Github (muschellij2/knitr@f5af631)
#> lattice 0.20-38 2018-11-04 [1] CRAN (R 3.6.2)
#> magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
#> Matrix 1.2-18 2019-11-27 [1] CRAN (R 3.6.2)
#> matrixStats 0.55.0 2019-09-07 [1] CRAN (R 3.6.0)
#> mgcv 1.8-31 2019-11-09 [1] CRAN (R 3.6.2)
#> mime 0.8 2019-12-19 [1] CRAN (R 3.6.0)
#> neurobase * 1.30.0 2020-02-07 [1] local
#> nlme 3.1-142 2019-11-07 [1] CRAN (R 3.6.2)
#> oro.nifti * 0.10.2 2020-02-05 [1] local
#> pillar 1.4.3 2019-12-20 [1] CRAN (R 3.6.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 3.6.0)
#> plyr 1.8.5 2019-12-10 [1] CRAN (R 3.6.0)
#> purrr 0.3.3 2019-10-18 [1] CRAN (R 3.6.0)
#> R.matlab 3.6.2 2018-09-27 [1] CRAN (R 3.6.0)
#> R.methodsS3 1.7.1 2016-02-16 [1] CRAN (R 3.6.0)
#> R.oo 1.23.0 2019-11-03 [1] CRAN (R 3.6.0)
#> R.utils 2.9.0 2019-06-13 [1] CRAN (R 3.6.0)
#> R6 2.4.1 2019-11-12 [1] CRAN (R 3.6.0)
#> Rcpp 1.0.3 2019-11-08 [1] CRAN (R 3.6.0)
#> RcppEigen 0.3.3.7.0 2019-11-16 [1] CRAN (R 3.6.0)
#> reprex 0.3.0.9001 2020-01-05 [1] Github (tidyverse/reprex@5ae0b29)
#> rlang 0.4.2 2019-11-23 [1] CRAN (R 3.6.0)
#> rmarkdown 2.0.7 2020-01-17 [1] Github (rstudio/rmarkdown@2faf16a)
#> RNifti * 1.0.1 2019-11-27 [1] CRAN (R 3.6.0)
#> rstudioapi 0.10.0-9003 2020-01-05 [1] Github (rstudio/rstudioapi@abe596d)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0)
#> stapler 0.7.1 2020-02-07 [1] local
#> stringi 1.4.5 2020-01-11 [1] CRAN (R 3.6.0)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0)
#> styler 1.1.1 2019-05-06 [1] CRAN (R 3.6.0)
#> tibble 2.1.3 2019-06-06 [1] CRAN (R 3.6.0)
#> WhiteStripe 2.3.2 2019-10-01 [1] local
#> withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0)
#> xfun 0.11 2019-11-12 [1] CRAN (R 3.6.0)
#> xml2 1.2.2 2019-08-09 [1] CRAN (R 3.6.0)
#> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.6.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library |
|
@muschellij2 The proposed solution works for me. Thank you for your help. I managed to face my dataset. We can close this issue. |
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I tried to deface some T1w images (brain and spine up to C7 level). The problem is that the images are cropped to C2 level in the spine.
Is there a way to enlarge the FOV of the pydeface ?
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