abpBrainExtraction fails

[vnckppl]

Issue
I am running abpBrainExtraction on a T1-weighted image that has previously been processed with abpN4. I use OASIS-30 data as template and mask.

I run the following code:

# Load template image and mask
tem <- antsImageRead(
  "/software/templates/OASIS-30/T_template0.nii.gz"
)
temmask <- antsImageRead(
  "/software/templates/OASIS-30/T_template0_BrainCerebellumMask.nii.gz"
)

# Load T1w data
myT1 <- antsImageRead("/data/in/T1w_n4.nii.gz")

# Build brain mask
mask <- abpBrainExtraction(
  img = myT1,
  tem = tem,
  temmask = temmask,
  tdir = "/data/in"
)

This results in:

source("example.R")
 bad det -1 v 1 u -1
 bad det -1 v 1 u -1 new 1
 bad det -1 v 1 u -1
 bad det -1 v 1 u -1 new 1

 *** caught segfault ***
address (nil), cause 'memory not mapped'

Traceback:
 1: antsImageHeaderInfo(filename)
 2: doTryCatch(return(expr), name, parentenv, handler)
 3: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 4: tryCatchList(expr, classes, parentenv, handlers)
 5: tryCatch(antsImageHeaderInfo(filename), error = function(e) return(NA))
 6: antsImageRead(x, ...)
 7: FUN(X[[i]], ...)
 8: FUN(X[[i]], ...)
 9: lapply(x, check_ants, ... = ...)
10: FUN(X[[i]], ...)
11: FUN(X[[i]], ...)
12: lapply(x, check_ants, ... = ...)
13: check_ants(image)
14: check_ants(image)
15: antsImageWrite(mask, "/data/in/mymask.nii.gz")
16: eval(ei, envir)
17: eval(ei, envir)
18: withVisible(eval(ei, envir))
19: source("example.R")

OS and Software versions:

• OS: Debian GNU/Linux bullseye/sid"
• R: R version 3.6.3
• ITKR_0.5.3
• ANTsR_0.5.4.2
• ANTsRCore_0.7.4

[dorianps]

Looks to me like you don't have enough memory/ram. What are the specs of your system.

…

On Mon, May 11, 2020, 1:23 PM vnckppl ***@***.***> wrote: *Issue* I am running abpBrainExtraction on a T1-weighted image that has previously been processed with abpN4. I use OASIS-30 data as template and mask. I run the following code: # Load template image and mask tem <- antsImageRead( "/software/templates/OASIS-30/T_template0.nii.gz" ) temmask <- antsImageRead( "/software/templates/OASIS-30/T_template0_BrainCerebellumMask.nii.gz" ) # Load T1w data myT1 <- antsImageRead("/data/in/T1w_n4.nii.gz") # Build brain mask mask <- abpBrainExtraction( img = myT1, tem = tem, temmask = temmask, tdir = "/data/in" ) This results in: source("example.R") bad det -1 v 1 u -1 bad det -1 v 1 u -1 new 1 bad det -1 v 1 u -1 bad det -1 v 1 u -1 new 1 *** caught segfault *** address (nil), cause 'memory not mapped' Traceback: 1: antsImageHeaderInfo(filename) 2: doTryCatch(return(expr), name, parentenv, handler) 3: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 4: tryCatchList(expr, classes, parentenv, handlers) 5: tryCatch(antsImageHeaderInfo(filename), error = function(e) return(NA)) 6: antsImageRead(x, ...) 7: FUN(X[[i]], ...) 8: FUN(X[[i]], ...) 9: lapply(x, check_ants, ... = ...) 10: FUN(X[[i]], ...) 11: FUN(X[[i]], ...) 12: lapply(x, check_ants, ... = ...) 13: check_ants(image) 14: check_ants(image) 15: antsImageWrite(mask, "/data/in/mymask.nii.gz") 16: eval(ei, envir) 17: eval(ei, envir) 18: withVisible(eval(ei, envir)) 19: source("example.R") *OS and Software versions:* - OS: Debian GNU/Linux bullseye/sid" - R: R version 3.6.3 - ITKR_0.5.3 - ANTsR_0.5.4.2 - ANTsRCore_0.7.4 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#315>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ACFJU7K5UKPBFTA6NWLPAL3RRAYAPANCNFSM4M6DCTPQ> .

[vnckppl]

I run R in a Docker container on OSX. The system itself has 16gb of ram, with 10gb allocated to Docker and 1Gb Swap. I think this should be sufficient, but correct me if I am wrong. I even upped the swap to 2gb and re-ran the script, but I get the exact same errors.

[dorianps]

Then I don't know what can be. Have you properly mounted the folders in /software and /data/in/ ? Looks like it's failing when trying to read some image headers.

…

On Mon, May 11, 2020, 2:03 PM vnckppl ***@***.***> wrote: I run R in a Docker container on OSX. The system itself has 16gb of ram, with 10gb allocated to Docker and 1Gb Swap. I think this should be sufficient, but correct me if I am wrong. I even upped the swap to 2gb and re-ran the script, but I get the exact same errors. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#315 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ACFJU7JDFS4JDVVYMJIPLEDRRA4VTANCNFSM4M6DCTPQ> .

[vnckppl]

I think I have. When I manually enter the container with docker run -it -v /some/local/folder:/data/in --entrypoint=/bin/bash someContainerID I can read and write to the local folder without any issues.
Also, when I run R from within the container, I have no issues reading and writing images.
Moreover, apbN4, antsRegistration, and ants_brain_extract (ANTsRNet) all run fine from within the container.

[muschellij2]

Can you try n4BiasCorrection, with and without a mask, and see if that works? Also - please confirm that "/data/in/mymask.nii.gz" does not currently exist. Best, John

…

On Mon, May 11, 2020 at 2:22 PM vnckppl ***@***.***> wrote: I think I have. When I manually enter the container with docker run -it -v /some/local/folder:/data/in --entrypoint=/bin/bash I can read and write to the local folder without any issues. Also, when I run R from within the container, I have no issues reading and writing images. Moreover, apbN4, antsRegistration, and ants_brain_extract (ANTsRNet) all run fine from within the container. — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#315 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAIGPLX55VZ4FZBQK2HSZT3RRA65HANCNFSM4M6DCTPQ> .

[vnckppl]

Starting the container with:

docker run -it \
       -v /some/local/input/folder:/data/in:ro \
       -v /some/local/output/folder:/data/out \
       --entrypoint=/bin/bash \
       someContainerID

and then running R, sourcing the following code:

## * Load Library
library("ANTsR")


## * Load data
base <- "/data/in"

myt1w <- antsImageRead(
  file.path(base, "T1w_n4.nii.gz")
)
myt1w_mask <- antsImageRead(
  file.path(base, "T1w_n4_mask.nii.gz")
)


## * Run N4 correction on entire image
# Ouptut folder
out_dir <- "/data/out/N4_noMask"
dir.create(out_dir)
# Run N4
output_image <- n4BiasFieldCorrection(myt1w, verbose = TRUE)
# Save output file
outfile <- file.path(out_dir, "N4_noMask.nii.gz")
antsImageWrite(output_image, outfile)



## * Run N4 correction within brain mask
# Ouptut folder
out_dir <- "/data/out/N4_withinMask"
dir.create(out_dir)
# Run N4
output_image <- n4BiasFieldCorrection(myt1w, myt1w_mask, verbose = TRUE)
# Save output file
outfile <- file.path(out_dir, "N4_withinMask.nii.gz")
antsImageWrite(output_image, outfile)

runs fine and produces the two expected N4 corrected images.

[muschellij2]

Sorry - I mean N4 passing in the mask, such as n4BiasFieldCorrection(img, mask = mask) Best, John

…

On Mon, May 11, 2020 at 3:44 PM vnckppl ***@***.***> wrote: Starting the container with: docker run -it \ -v /some/local/input/folder:/data/in:ro \ -v /some/local/output/folder:/data/out \ --entrypoint=/bin/bash \ someContainerID and then running R, sourcing the following code: ## * Load Library library("ANTsR") ## * Load mask data base <- "/data/in" myt1w <- antsImageRead( file.path(base, "T1w_n4.nii.gz") ) myt1w_mask <- antsImageRead( file.path(base, "T1w_n4_mask.nii.gz") ) ## * Run N4 correction on entire image # Ouptut folder out_dir <- "/data/out/N4_noMask" dir.create(out_dir) # Run N4 output_image <- n4BiasFieldCorrection(myt1w, verbose = TRUE) # Save output file outfile <- file.path(out_dir, "N4_noMask.nii.gz") antsImageWrite(output_image, outfile) ## * Run N4 correction on entire image # Ouptut folder out_dir <- "/data/out/N4_withinMask" dir.create(out_dir) # Run N4 output_image <- n4BiasFieldCorrection(myt1w, verbose = TRUE) # Save output file outfile <- file.path(out_dir, "N4_withinMask.nii.gz") antsImageWrite(output_image, outfile) runs fine and produces the two expected N4 corrected images. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#315 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAIGPLXKMD44BZOMAAGVBDTRRBISNANCNFSM4M6DCTPQ> .

[vnckppl]

Hi John,
I did (and have updated my previous post).
Same results, i.e., this runs smoothly.

[muschellij2]

Only way likely is to share the image. Best, John

…

On Mon, May 11, 2020 at 4:12 PM vnckppl ***@***.***> wrote: Hi John, I did (and have updated my previous post). Same results, i.e., this runs smoothly. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#315 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAIGPLVN5QJ7BZWNVKR74HLRRBL2BANCNFSM4M6DCTPQ> .

[vnckppl]

I am getting the same error with a default template that comes with FSL, so I guess the image itself is not the problem. I am further investigating the issue. I am building a virtual environment with ANTsR using Packrat so that I can try and see if a different setup produces the same error. However, I am running into some other issues with install_github("stnava/ANTsR") for which I have opened another thread here.

[vnckppl]

I figured out what went wrong. I was expecting abpBrainExtraction to write out an antsImage, but it is writing out a list. When I tried to write out the list as an antsImage, R throws the memory error:

 *** caught segfault ***
address (nil), cause 'memory not mapped'

Everything works now, and the masks look good. For some image, I do see this warning/error in the terminal though:

 bad det -1 v -1 u 1
 bad det -1 v -1 u 1 new 1
 bad det -1 v -1 u 1
 bad det -1 v -1 u 1 new 1

Should I be worried about that?

[dorianps]

That warning happens often but I haven't seen bad results when it appears.

…

On Tue, May 12, 2020, 1:04 PM vnckppl ***@***.***> wrote: Closed #315 <#315>. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#315 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ACFJU7IF4M7PL7XS5DFCUXTRRF6QVANCNFSM4M6DCTPQ> .

[cookpa]

Those errors come from antsAI. It is a multi-start optimizer that tries a bunch of rotations and translations to initialize registrations. Some of them will be so far off from the right solution that they fail. If you see hundreds of them, it might be a problem, but a few are expected.