[micaceous]

Thank you for the detailed response and materials.

If you don’t mind, more remaining thing to clarify..so does this mean that the only provided bval (fileprefix.dwi.bval) and bvec (fileprefix.dwi.RAS.bvec) files in the regular output are technically incorrect for the distortion corrected diffusion data (fileprefix.dwi.RAS.correct.nii.gz) in native diffusion space? (not T1 space). Or are they correct, and they would only be incorrect if tried to apply to diffusion data in T1 space?

[micaceous]

So far I’ve tested BDP on 3 different datasets (2 of which used to run successfully on another linux system), and all produce the same mask error, so it seems likely it’s not truly a mask problem. I’m guessing it has something to do with the fact that I’m running BrainSuite on Bash on Ubuntu on Windows, or because I had to do that “execstack” code fix earlier.

[micaceous]

Btw, I rebooted my computer and I didn’t need to do that “execstack” code again in order to get BDP to run…although it’s possible that this “execstack” fix I found for my previous LD_LIBRARY_PATH error may be causing this BDP mask error I’m having now. What do you think?

[micaceous]

Hi, thank you. I’m not sure yet how to put my image as http link, I will figure that out. But wouldn’t you also need my dwi and t1 files to see if you can recreate the errors on your end?

So to answer your questions…
– I used the same mask as before
– I tried without the dwi-mask option, still throws an error (see below):

Below is the log output from trying to run BDP without the –dwi-mask option:

BDP Version: 17a (build #0072), released 2017-06-22

================================================================================
Setting up dataset and inputs
================================================================================
Reading input flags…

Checking input files…

Processing data with fileprefix:
/mnt/y/jdelly_dti/DTIpipeline_Version2/86_f000_Acute/86_f000_Acute_anat_brain_RAS

================================================================================
Co-registration and Distortion Correction
================================================================================
Reading the input parameters for co-registration…
Total memory (physical+swap) found: 181.09GB

Checking orientation information…Done
Extracting 0-diffusion (b=0) image from input DWIs…

DWI mask is not defined in input flags. BDP will try to estimate a (pseudo) mask
from 0-diffusion (b=0) image. Automatic mask estimation may not be accurate in
some sitations and can affect overall quality of co-registration. In case
co-registration is not accurate, you can define a DWI mask by using flag
–dwi-mask <mask_filename>. The mask can be generated and hand edited in
BrainSuite interface. This mask would be used only for registration purposes
(and not for statistics computation).

***************************************
* *
* Error running BDP *
* *
* AUTO-MASKING FAILED *
* *
***************************************

Error message:
BDP encountered an error while estimating the brain-mask for the input diffusion
volume.

Error help/resolution:
Please define a mask for diffusion volume by using flag –dwi-mask
<mask_filename>. The mask can be generated and hand edited in BrainSuite
interface.

***************************************

[micaceous]

Hi, any more ideas on what may be causing this mask error? I’m close to running out of time on this. Any more info I can give you? Many thanks!

[micaceous]

Some more info that might be helpful…when BDP terminates with this mask error, it has created the following files, and two of these (86_f000_Acute_anat_brain_RAS.dwi.RAS.rearranged.b0s.nii, and 86_f000_Acute_anat_brain_RAS.bfc.nii) are not present in the BDP output from before when I had it working on another system (perhaps these are intermediate files which get cleaned up after, just thought I’d mention it).

86_f000_Acute_anat_brain_RAS.dwi.RAS.rearranged.b0s.nii.gz
86_f000_Acute_anat_brain_RAS.bfc.nii.gz
86_f000_Acute_anat_brain_RAS.dwi.bmat
86_f000_Acute_anat_brain_RAS.dwi.RAS.bmat
86_f000_Acute_anat_brain_RAS.dwi.RAS
86_f000_Acute_anat_brain_RAS.dwi.RAS.nii.gz

[micaceous]

Yes certainly, I will report back on the execstack once I can reboot my computer.

Regarding mask, yes the t1 mask looks good as well. In fact, I ran BDP successfully on these data before (on another linux system), and during my current tests all the code and data files are exactly the same, so it’s quite strange. It’s not recognizing that I’m submitting the –dwi-mask flag.

Here is BDP log…

BDP Version: 17a (build #0072), released 2017-06-22

================================================================================
Setting up dataset and inputs
================================================================================
Reading input flags…

Checking input files…

Processing data with fileprefix:
86_f000_Acute_anat_brain_RAS

================================================================================
Co-registration and Distortion Correction
================================================================================
Reading the input parameters for co-registration…
Total memory (physical+swap) found: 181.09GB

Checking orientation information…Done
Extracting 0-diffusion (b=0) image from input DWIs…

***************************************
* *
* Error running BDP *
* *
* AUTO-MASKING FAILED *
* *
***************************************

Error message:
BDP encountered an error while estimating the brain-mask for the input diffusion
volume.

Error help/resolution:
Please define a mask for diffusion volume by using flag –dwi-mask
<mask_filename>. The mask can be generated and hand edited in BrainSuite
interface.

***************************************

[micaceous]

Almost successful…perhaps the following errors are related to my previous problems somehow?

I’m getting an auto-masking failure error, which terminates bdp.sh

“BDP encountered an error while estimating the brain-mask for the input diffusion volume…Please define a mask for diffusion volume by using flag –dwi-mask <mask_filename>. The mask can be generated and hand edited in BrainSuite interface”

The strange thing is that I am including the –dwi-mask option, see my code below (note, this post shows two hyphens as one). And I rechecked that the mask is anatomically correct.

/mnt/c/Users/Micaceous/Desktop/Research/Programs/BrainSuite17a/bdp/bdp.sh 86_f000_Acute_anat_brain_RAS.bfc.nii.gz –dir=y –tensors –FRACT –t1-mask 86_f000_Acute_anat_brain_RAS.bfc.mask.nii.gz –dwi-mask 86_f000_Acute_dwi_QCed_fixorient_nodif_brain_mask.nii.gz –nii 86_f000_Acute_dwi_QCed_fixorient.nii.gz -g 86_f000_Acute_bvecs_QCed.txt -b 86_f000_Acute_bvals_QCed.txt

Any ideas?

[micaceous]

Alright, success! (it seems)

Here’s what I did:

sudo apt-get install execstack
sudo execstack -c /mnt/c/Users/Micaceous/Desktop/Research/Programs/matlab_compiler_runtime_R2015b/v90/bin/glnxa64/lib*

I think I saw a source online saying that this might be necessary after every time I reboot my computer, do you think so? Would there be an easy way around this? (perhaps by simply adding that last code to my script?)

[micaceous]

I found a potential clue about clearing the executable stack, see link below for an example…could this be it? I’m going to try but not 100% sure how to do it correctly

https://stackoverflow.com/questions/39136040/python3-4-error-cannot-enable-executable-stack-as-shared-object-requires-inva

[micaceous]

I did chmod -R 777 on my mcr directory (/mnt/c/Users/Micaceous/Desktop/Research/Programs/matlab_compiler_runtime_R2015b/v90) and still same error. [yup I put “/my/path” just for the forum]

I’ve rechecked all my paths so many times…the bdp.sh help on command line so I know it’s referenced correctly, and BFC works. And when I try to run bdp.sh, I’m not getting either of the error messages found inside the bdp.sh (“BDP could not locate…” or “BDP Could not find a valid…”), so I think this means that the runtime directory is referenced correctly

[micaceous]

Could it be something about compatibility of new BrainSuite17a version with my system (I’m running Bash on Ubuntu on Windows)? If no other ideas to fix with 17a, I could try with 16a1

[micaceous]

Btw, although the MCR install instructions said to modify the LD_LIBRARY_PATH in bash profile, it does not seem to matter because bdp.sh already does this at the bottom of the script. I was worried that additionally adding it to my .bashrc was interfering somehow, so I removed it from .bashrc but the same error message appears so seems irrelevant.

[micaceous]

Thanks for the reply. Yes I forgot to say, I definitely already followed those instructions, redefining it as follows…

BrainSuiteMCR=”/mnt/c/Users/Micaceous/Desktop/Research/Programs/matlab_compiler_runtime_R2015b/v90″;

– it’s correct to end with v90 right?

Both files (referenced in error) exist (in the proper subdirectory that they mention):
libmwblas.so
libmwmclbase.so

Don’t know if this is a problem, but the following directories (referring to the LD_LIBRARY_PATH section at end of bdp.sh) do NOT exist in my mcr folders:
${BrainSuiteMCR}/sys/java/jre/glnxa64/jre/lib/amd64/native_threads
${BrainSuiteMCR}/sys/java/jre/glnxa64/jre/lib/amd64/client
${BrainSuiteMCR}/X11

[micaceous]

I just realized that Bhushan et al. (2012) is your manuscript, very cool, I enjoyed reading it! I’m curious to know, because I don’t quite understand everything in it…given that, in my current situation, the voxel size transformation going from larger DWI (1x1x2mm) to smaller T1 (1x1x1mm) practically doubles the in-plane resolution of DWI, does the interpolation essentially create new diffusion data that didn’t exist before? If so, how does it do that? (sorry I know that’s a vague question, but perhaps there’s a paper you could point me to?). I’m guessing it doesn’t duplicate the information in a single 2mm DWI slice into the two 1mm T1 slices right?

I’m wondering this because I’ve always previously performed tractography and analysis in native diffusion space, and so I’m curious to know how doing it in native T1 space will affect it. Perhaps there are some specific disadvantages or trade-offs? But even if so, I have such bad distortion in this dwi data (and I have no field map or double acquisition), that I think BrainSuite’s method will confer substantial improvement.

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