address non repro of antsBET in tests and in the meta

scilus · Dec 3, 2024 · 937e5d8 · 937e5d8
1 parent 626524c
commit 937e5d8
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diff --git a/subworkflows/nf-neuro/preproc_t1/meta.yml b/subworkflows/nf-neuro/preproc_t1/meta.yml
@@ -8,7 +8,9 @@ description: |
   The resulting T1 is corrected, resampled, brain extracted and cropped.
   You can retrieve the file after each step if you don't want to run the entire subworkflow.
   The next steps would be to register the resulting T1-corrected image with the DWI-corrected image
-  with, for example, the REGISTRATION subworkflow.
+  with, for example, the REGISTRATION subworkflow. IMPORTANT : the module is only reproducible with
+  ANTs when BET is run using a single thread. For performance and reproducibility, use the other
+  available methods.
   -----------  Steps  -----------
   Denoising (nlmeans, scil).
     Used to remove the noise induced by the MRI acquisition,
@@ -23,7 +25,8 @@ description: |
     This spatial resolution is modifiable in the configuration file.
   Brain Extraction (bet, ANTs, freesurfer).
     Isolates the brain tissue voxels from the remaining image. Also creates a binary brain mask.
-    This brain extraction is required for the T1 to DWI Registration.
+    This brain extraction is required for the T1 to DWI Registration. IMPORTANT : when using ANTs,
+    brain extraction is reproducible only when run using a single thread.
   Cropping (scil).
     Crops the empty planes around the brain to optimize the next processing steps.
   Subworkflow based on Tractoflow : https://www.sciencedirect.com/science/article/pii/S105381192030375X?via%3Dihub

diff --git a/subworkflows/nf-neuro/preproc_t1/tests/main.nf.test b/subworkflows/nf-neuro/preproc_t1/tests/main.nf.test
@@ -88,11 +88,11 @@ nextflow_workflow {
                     niftiMD5SUM(workflow.out.image_nlmeans.get(0).get(1)),
                     niftiMD5SUM(workflow.out.image_N4.get(0).get(1)),
                     niftiMD5SUM(workflow.out.image_resample.get(0).get(1)),
-                    niftiMD5SUM(workflow.out.image_bet.get(0).get(1)),
-                    niftiMD5SUM(workflow.out.mask_bet.get(0).get(1)),
+                    file(workflow.out.image_bet.get(0).get(1)).name,
+                    file(workflow.out.mask_bet.get(0).get(1)).name,
                     workflow.out.crop_box,
-                    niftiMD5SUM(workflow.out.mask_final.get(0).get(1)),
-                    niftiMD5SUM(workflow.out.t1_final.get(0).get(1)),
+                    file(workflow.out.mask_final.get(0).get(1)).name,
+                    file(workflow.out.t1_final.get(0).get(1)).name,
                     workflow.out.versions
                 ).match()}
             )