Releases: spinalcordtoolbox/spinalcordtoolbox
Release list
7.3
Notable changes include:
- Feature: Add deep learning-based motion correction algorithm (
-dlflag) tosct_dmri_mocoandsct_fmri_moco. View pull request - Feature: Implement
length_anteriorandlength_posteriormetrics insct_process_segmentation. View pull request - Enhancement: Reduce memory usage in
sct_apply_transfowhen warping 4D images by avoiding unnecessary data copies. View pull request - Enhancement: Handle missing centerline slices in
sct_compute_ascorandsct_process_segmentationby limiting segmentation metrics to only overlapping slices. View pull request - Bug: Fix excessive RAM usage and slow processing in
sct_process_segmentationby resampling after cropping rather than before. View pull request - Bug: Fix blank QC report page by improving rendering performance for large reports. View pull request
- Bug: Fix bug in
sct_analyze_lesionwhere thevert_levelcolumn would sometimes be incorrectly included in thetotal % all_tractssum when using-f -perslice 1. View pull request - Bug: Fix several bugs with the
find_angle_hogfunction insct_register_to_templateto make computed HOG values consistent. View pull request - Bug: Avoid crash in
sct_deepsegduring inference ifspineis present in the$SCT_DIRpath. View pull request - Installation: Fix several bugs in
sct.defto improve Apptainer installation (install directory, task installation). View pull request - Documentation: Update web tutorials to include changes to the slides from the 2025 SCT Course. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 22.04
~~~
Version: git-HEAD-58ee6233f29d9318e23f566654b8316e5d228643
Ran on: Linux runnervmeorf1 6.17.0-1010-azure
Duration: 0hrs 39min 4sec
---
t2/csa_c2c3.csv: 72.68227484642557 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.4713778935507 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.64065515466891 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126165 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.399745947796255 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7663495392134614 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7700597393353209 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 15 (Sequoia)
~~~
Version: git-HEAD-58ee6233f29d9318e23f566654b8316e5d228643
Ran on: Darwin sat12-bq158-dfb543bb-77e1-4927-9324-89bd2f90f8b8-FEA3689B3F3F.local 24.6.0
Duration: 2hrs 1min 28sec
---
t2/csa_c2c3.csv: 72.68227484642557 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.4713778935507 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.64065515466891 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126165 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.39395223720682 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7679826165930632 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7670177237594403 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2025
~~~
Version: git-HEAD-58ee6233f29d9318e23f566654b8316e5d228643
Ran on: MINGW64_NT-10.0-26100 runnervmlt4x0 3.6.7-fb42d713.x86_64
Duration: 0hrs 46min 53sec
---
batch_processing.sh: line 270: D:\a\spinalcordtoolbox\spinalcordtoolbox/python/envs/venv_sct/bin/python: No such file or directory
t2/csa_c2c3.csv: 72.68227484642557 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.4713778935507 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.64065515466891 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126165 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.399745947796255 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7663495392134614 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7700597393353209 [Row 2, WA()]
~~~
7.2
Important
Version 7.2 of SCT was yanked due to excessive RAM usage in the sct_process_segmentation script (#5129).
This issue was fixed in Version 7.3, and so we recommend that you migrate to this version.
7.1
Notable changes include:
- Installation: Add support for Apptainer installations for use on HPC systems. View pull request
- Installation: Update SCT's virtual environment to use Python 3.10 instead of 3.9. View pull request
- Feature: Implement "tissue bridge ratio" metrics in
sct_analyze_lesion. View pull request - Feature: Add flag
-discfiletosct_process_segmentationto allow for determiningVertLevelusing projected disc labels. View pull request - Enhancement: Update
lesion_msDeepSeg model from r20241101 to r20250626 (ESMRMB 2025). View pull request - Enhancement: Use centerline of
-vertfileinsct_extract_metricfor more accurate mapping ofVertLevelto z slices. View pull request - Bug: Prevent repeated slices during the straightening step of template registration by correctly zeroing out duplicate slices in the warping field. View pull request
- Bug: Prevent "phantom copy" of registered image by masking output of
sct_apply_transfowhen applying-initwarpduring multimodal registration. View pull request - Documentation: Update and reorganize Docker installation instructions. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 24.04
~~~
Version: git-HEAD-c2a0facd9df0354ef977cb8fc5b07a7f09757272
Ran on: Linux pkrvmubgrv54qmi 6.11.0-1018-azure
Duration: 0hrs 27min 46sec
---
t2/csa_c2c3.csv: 72.68184387488087 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.46904777045916 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.61845955633323 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126166 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.406838543730174 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.766017958604616 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7686029827193743 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 13 (Ventura)
~~~
Version: git-HEAD-c2a0facd9df0354ef977cb8fc5b07a7f09757272
Ran on: Darwin Mac-1755286127678.local 22.6.0
Duration: 0hrs 33min 33sec
---
t2/csa_c2c3.csv: 72.68184387488087 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.46904777045916 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.61845955633323 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126166 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.41732502666166 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7680962966783638 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7662131173108033 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2025
~~~
Version: git-HEAD-c2a0facd9df0354ef977cb8fc5b07a7f09757272
Ran on: MINGW64_NT-10.0-26100 runnervmw77sl 3.6.3-7674c51e.x86_64
Duration: 0hrs 32min 28sec
---
batch_processing.sh: line 270: C:\a\spinalcordtoolbox\spinalcordtoolbox/python/envs/venv_sct/bin/python: No such file or directory
t2/csa_c2c3.csv: 72.68184387488087 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.46904777045916 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.61845955633323 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126166 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.406838543730174 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.766017958604616 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7686029827193743 [Row 2, WA()]
~~~
7.0
Important
Initial release: 2025-04-24
Last updated: 2025-05-08 (⚠️ New! ⚠️: QC Report hotfix.)
Notable changes include:
- Feature: Reworked
sct_deepsegsyntax, interface, and model names. View pull request- Add
lesion_ms_axial_t2model tosct_deepsegfor MS lesion/SC segmentation of axial T2 images. View pull request - Add
graymattermodel tosct_deepsegfor contrast-agnostic segmentation of the gray matter. View pull request - Update
spinalcordcontrast-agnostic model to retrain from scratch using nnUNetv2 framework. View pull request - Update
rootletsT2 model to now segment MP2RAGE images as well. View pull request
- Add
- Feature Add new CLI tool (
sct_detect_compression) to predict compression probability. View pull request - Feature: Add
-lrootletargument tosct_register_to_templateto enable rootlets-informed registration. View pull request - Feature: Add detailed time and memory profiling to all CLI scripts. View pull request
- Enhancement: Overhaul the QC report backend to use modern web technologies. View pull request
- Enhancement: Update PAM50 to include changes to
PAM50_rootlets.nii.gz(ventral rootlets, Th1 level). View pull request - Enhancement: Recompute PAM50 normalized metrics using the newest
spinalcordsegmentation model. View pull request - Installation: Adopt Miniforge environment manager to address Miniconda licensing concerns. View pull request
- Documentation: Update web tutorials to match the changes made for the 2024 SCT Course. View pull request
- Testing: Add new GitHub Actions workflow to ensure that older releases install without error. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 24.04
~~~
Version: git-master-ab2e0af5decd20c1819772c94965dc83ed19d480
Ran on: Linux fv-az1665-569 6.11.0-1012-azure
Duration: 0hrs 28min 23sec
---
t2/csa_c2c3.csv: 72.68184387488087 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.46904777045916 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.61845955633323 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126166 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.406838543730174 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.766017958604616 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7686029827193743 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 13 (Ventura)
~~~
Version: git-master-ab2e0af5decd20c1819772c94965dc83ed19d480
Ran on: Darwin Mac-1745491757000.local 22.6.0
Duration: 0hrs 36min 50sec
---
t2/csa_c2c3.csv: 72.68184387488087 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.46904777045916 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.61845955633323 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126166 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.41732502666166 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7680962966783638 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7662131173108033 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2022
~~~
Version: git-master-ab2e0af5decd20c1819772c94965dc83ed19d480
Ran on: MINGW64_NT-10.0-20348 fv-az972-102 3.5.7-463ebcdc.x86_64
Duration: 0hrs 32min 22sec
---
t2/csa_c2c3.csv: 72.68184387488087 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 72.46904777045916 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 33.61845955633323 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.804074575866881 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 61.40141843126166 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.406838543730174 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.766017958604616 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7686029827193743 [Row 2, WA()]
~~~
6.5
Important
Initial release: 2024-12-03
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)
Notable changes include:
- Documentation: Add model gallery for
sct_deepseg. View pull request - Feature: Add contrast-agnostic MS lesion segmentation model to
sct_deepseg. View pull request - Feature: Add canal segmentation model to
sct_deepseg. View pull request and follow-up pull request - Feature: Add TotalSpineSeg model (vertebrae, intervertebral discs, spinal cord, and spinal canal) to
sct_deepseg. View pull request - Feature: Output lesion length and width for the midsagittal slice in
sct_analyze_lesion. View pull request - Enhancement: Update version of contrast agnostic model in
sct_deepsegto r20241024 (improved for SCI and whole-spine T1/T2 images). View pull request - Refactoring: Retire outdated DeepSeg models (
seg_sc_ms_lesion_stir_psir,ms_sc_mp2rage). View pull request - Documentation: Split "Command Line Tools" page into multiple individual pages (with markdown formatting). View pull request
- Many other minor bugfixes and improvements (especially for QC reports).
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 20.04
Version: git-HEAD-8c7e14fbb6da0cd4a289afd867781e415e4f4917
Ran on: Linux fv-az1981-407 5.15.0-1074-azure
Duration: 0hrs 18min 3sec
---
t2/csa_c2c3.csv: 73.90440963005199 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.789823839063319 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.44251331713387 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.43643151888196 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7781131912645235 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7763355209248591 [Row 2, WA()]
Results of batch_processing.sh on macOS 13 (Ventura)
Version: git-HEAD-8c7e14fbb6da0cd4a289afd867781e415e4f4917
Ran on: Darwin Mac-1733237830010.local 22.6.0
Duration: 0hrs 30min 12sec
---
t2/csa_c2c3.csv: 73.90440963005199 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.789823839063319 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.44251331713387 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.424413121632384 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7761467810610112 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7773244575039472 [Row 2, WA()]
Results of batch_processing.sh on Windows 2022
Version: git-HEAD-8c7e14fbb6da0cd4a289afd867781e415e4f4917
Ran on: MINGW64_NT-10.0-20348 fv-az534-268 3.5.4-1e8cf1a5.x86_64
Duration: 0hrs 19min 10sec
---
batch_processing.sh: line 266: D:\a\spinalcordtoolbox\spinalcordtoolbox/python/envs/venv_sct/bin/python: No such file or directory
t2/csa_c2c3.csv: 73.90440963005199 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.789823839063319 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.44251331713387 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.43643151888196 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7781131912645235 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7763355209248591 [Row 2, WA()]
6.4
Important
Initial release: 2024-08-08
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)
Notable changes include:
- Feature: Add midsagittal tissue bridges to
sct_analyze_lesion. View pull request - Feature: Support custom labels from
info_label.txtforsct_analyze_lesion -f. View pull request - Feature: Add slicewise analysis for
sct_analyze_lesion -f. View pull request - Feature: Track
sct_deepsegmodel provenance withsource.json(in model folder) and JSON sidecar (in output). View pull request - Feature: Add T2w dog template to
sct_download_data. View pull request - Enhancement: Update contrast agnostic
sct_deepsegmodel to v2.4 (now improved for lumbar t2w + PSIR/STIR images). View pull request - Enhancement: Update SCI
sct_deepsegmodel to SCIsegV2. View pull request - Enhancement: Improve
sct_deepsegrootlets seg QC report by improving the cropping, centering, and colormap. View pull request - Enhancement: Use
LazyLoaderclass to minimize startup time for all CLI scripts. View pull request - Bug: Fix straightening transformations for images with "tilted" qform/sform. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 20.04
~~~
Version: git-master-44471c6bfb2d9c9bb507dd6a99120db4508db84a
Ran on: Linux fv-az2030-237 5.15.0-1068-azure
Duration: 0hrs 15min 6sec
---
t2/csa_c2c3.csv: 73.90440963005199 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.789823839063319 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.44251331713387 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.43643151888196 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7788101713862418 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7765826899727847 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 12 (Monterey)
~~~
Version: git-master-44471c6bfb2d9c9bb507dd6a99120db4508db84a
Ran on: Darwin Mac-1723200118668.local 21.6.0
Duration: 0hrs 19min 51sec
---
t2/csa_c2c3.csv: 73.90440963005199 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.789823839063319 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.44251331713387 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.424413121632384 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.779190298495622 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7762361654476364 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2019
~~~
Version: git-master-44471c6bfb2d9c9bb507dd6a99120db4508db84a
Ran on: MINGW64_NT-10.0-20348 fv-az534-455 3.4.10-87d57229.x86_64
Duration: 0hrs 18min 59sec
---
t2/csa_c2c3.csv: 73.90440963005199 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.789823839063319 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.44251331713387 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.43643151888196 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7788101713862418 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7765826899727847 [Row 2, WA()]
~~~
6.3
Important
Initial release: 2024-04-26
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)
Notable changes include:
- Feature: Add QC report for
sct_deepseg. View pull request - Feature: Add CanProCo-based MS lesion segmentation model to
sct_deepseg. View pull request - Feature: Add EPI-BOLD fMRI spinal cord segmentation model to
sct_deepseg. View pull request - Enhancement: Update
contrast-agnosticSC segmentation model (sct_deepseg) to the latest version (v2.3). View pull request - Enhancement: Switch to using mean magnitude for output
moco_params.tsvfile used for QC. View pull request - Documentation: Add links to new 2024 SCT review paper to prominent locations in documentation. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 20.04
~~~
Version: git-HEAD-f0e3766f4d663d28fbb6b718cd0f76bd203a0971
Ran on: Linux fv-az1533-44 5.15.0-1061-azure
Duration: 0hrs 16min 46sec
---
t2/csa_c2c3.csv: 73.87680055661444 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.515230379832953 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93314479093739 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.417007086785446 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7758118462499376 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.773312472697186 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 12 (Monterey)
~~~
Version: git-HEAD-f0e3766f4d663d28fbb6b718cd0f76bd203a0971
Ran on: Darwin Mac-1714066641279.local 21.6.0
Duration: 0hrs 21min 32sec
---
t2/csa_c2c3.csv: 73.87095978136215 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.515230379832953 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93314479093739 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.41827867818828 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7761900744878227 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7765149211365178 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2022
~~~
Version: git-HEAD-f0e3766f4d663d28fbb6b718cd0f76bd203a0971
Ran on: MINGW64_NT-10.0-20348 fv-az1105-632 3.4.10-87d57229.x86_64
Duration: 0hrs 22min 13sec
---
t2/csa_c2c3.csv: 73.87680055661444 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89183952519573 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530312082996 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.515230379832953 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93314479093739 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.417007086785446 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7758118462499376 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.773312472697186 [Row 2, WA()]
~~~
6.2
Important
Initial release: 2024-02-15
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)
Notable changes include:
- Feature: Integrate 4 new nnUNet/MONAI models into
sct_deepseg(contrast-agnostic softseg, SCI lesion/SC seg, spinal nerve rootlet seg, mouse GM/WM seg). View pull request - Feature: Save QC records to browser local storage to avoid losing data on refresh. View pull request
- Feature: Update PAM50 template to include new
PAM50_rootlets.nii.gzfile. View pull request - Bugfix: Fix straightening error during registration if 3+ labels are supplied and topmost disc label is not C1. View pull request
- Bugfix: Mitigate scaling issues (
1.0->0.999) due to float/int datatype mismatches between header and array. View pull request - Installation: Specify Rosetta 2 as a requirement for installation on Apple silicon (M1, M2, M3). View pull request
- Documentation: Port changes from SCT Course 2023 Google Slides to the web tutorials. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 20.04
~~~
Version: git-master-6962e03b5906ab3466e6e330438dbea58d949407
Ran on: Linux fv-az1018-974 5.15.0-1054-azure
Duration: 0hrs 17min 15sec
---
t2/csa_c2c3.csv: 73.8768043493825 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89184331879929 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530487782326 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487533885581323 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93464311280606 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.417007018368906 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7758118559608612 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7733124731836604 [Row 2, WA()]
~~~Results of batch_processing.sh on macOS 11 (Big Sur)
~~~
Version: git-master-6962e03b5906ab3466e6e330438dbea58d949407
Ran on: Darwin Mac-1708024085684.local 20.6.0
Duration: 0hrs 29min 31sec
---
t2/csa_c2c3.csv: 73.8709635738436 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89184331879929 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530487782326 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487533885581323 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93464311280606 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.41827830455262 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7761900951571409 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7765149187171309 [Row 2, WA()]
~~~Results of batch_processing.sh on Windows 2019
~~~
Version: git-master-6962e03b5906ab3466e6e330438dbea58d949407
Ran on: MINGW64_NT-10.0-17763 fv-az1488-920 3.4.9-be826601.x86_64
Duration: 0hrs 23min 38sec
---
batch_processing.sh: line 270: D:\a\spinalcordtoolbox\spinalcordtoolbox/python/envs/venv_sct/bin/python: No such file or directory
t2/csa_c2c3.csv: 73.8768043493825 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89184331879929 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.23530487782326 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487533885581323 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93464311280606 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.417007018368906 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7758118559608612 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7733124731836604 [Row 2, WA()]
~~~6.1
Important
Initial release: 2023-11-05
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)
This minor release of SCT has been developed in preparation for the 2023-10-20 SCT Course. It contains a significant update to the PAM50 template, important documentation improvements, and many other bugfixes and tweaks.
Notable changes include:
- Feature: Update PAM50 template link to include cord and lumbar label changes. View pull request
- Feature: Add function to output the axial damage ratio for
sct_analyze_lesion. View pull request - Documentation: Add tutorial for
sct_compute_compressionView pull request - Documentation: Add tutorial for lumbar segmentation and registration. View pull request
- Documentation: Update Docker installation instructions for Linux/macOS/Windows. View pull request
- Maintenance: Remove
-sfunctionality fromsct_warp_templateand add a deprecation warning. View pull request - Bugfix: Fix distorted registration due to straightening bug in
get_closest_to_absolute. View pull request - Bugfix Use pandas for
.csvsaving insct_compute_compressionto correctly merge existing output metric columns. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 20.04
~~~
Version: git-master-f5a46f328fe797b3d7c0e3844e17ad3f8add5ee1
Ran on: Linux fv-az619-734 5.15.0-1050-azure
Duration: 0hrs 26min 56sec
---
t2/csa_c2c3.csv: 73.87711295363036 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89298021190447 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.25734847835911 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.48783482885619 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93830702088245 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.39463563966487 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7793857114020448 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.775688329824498 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 11 (Big Sur)
~~~
Version: git-master-f5a46f328fe797b3d7c0e3844e17ad3f8add5ee1
Ran on: Darwin Mac-1699196155540.local 20.6.0
Duration: 0hrs 28min 56sec
---
t2/csa_c2c3.csv: 73.87711295363036 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89298021190447 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.25734847835911 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487834828856178 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93830702088249 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.41599937353151 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7807687336793107 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.774647306583997 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2019
~~~
Version: git-master-f5a46f328fe797b3d7c0e3844e17ad3f8add5ee1
Ran on: MINGW64_NT-10.0-17763 fv-az981-219 3.4.7-25de8b84.x86_64
Duration: 0hrs 22min 58sec
---
t2/csa_c2c3.csv: 73.87711295363036 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89298021190447 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.25734847835911 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487834828856178 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93830702088248 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.39462068731342 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7793857115174943 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7756883298906552 [Row 2, WA()]
~~~
SCT v6.0
Important
Initial release: 2023-07-14
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)
This major release provides significant improvements for how SCT is installed on all platforms, as well as many new features and bugfixes.
Notable changes include:
- Installation: Allow
install_sctto be run standalone (without downloading "Source code" archive). View pull request - Installation: Use Miniconda instead of built-in Python for Windows installations. View pull request
- Feature: Add new CLI script to compute normalized metric ratios (MSCC, etc.) for compressed levels. View pull request
- Feature: Add new
-histooption tosct_warp_templateto warp the newly-added PAM50 histology files. View pull request - Feature: Add new sagittal mosaic option for
sct_deepseg_lesionQC report. View pull request - Feature: Add support for model ensembles to
sct_deepsegand use it formp2rage_lesionmodel. View pull request - Feature: Add new
-project-centerlineoption tosct_label_utilsto project an image on the spinal cord centerline. View pull request - Feature: Add new
-centerline-softoption tosct_get_centerlineto output a non-binary "soft" centerline. View pull request - Bugfix: Ensure that qform/sform codes are preserved when generating
sct_deepseg_scsegmentation. View pull request
Full release notes and Changelog
Results of batch_processing.sh on Ubuntu 20.04
~~~
Version: git-master-908998829a2a3694fa96363b358c9b662da4ae43
Ran on: Linux fv-az205-332 5.15.0-1041-azure
Duration: 0hrs 23min 3sec
---
t2/csa_c2c3.csv: 73.87711295363036 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89298021190447 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.25734847835911 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487834828856178 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93830702088249 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.38856944000351 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7793405440192693 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7755611783165834 [Row 2, WA()]
~~~
Results of batch_processing.sh on macOS 11 (Big Sur)
~~~
Version: git-master-908998829a2a3694fa96363b358c9b662da4ae43
Ran on: Darwin Mac-1689358819888.local 20.6.0
Duration: 0hrs 39min 15sec
---
t2/csa_c2c3.csv: 73.87711295363036 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89298021190447 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.25734847835911 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487834828856178 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93830702088249 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.43230073944698 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7805537210812612 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7746193990233381 [Row 2, WA()]
~~~
Results of batch_processing.sh on Windows 2019
~~~
Version: git-master-908998829a2a3694fa96363b358c9b662da4ae43
Ran on: MINGW64_NT-10.0-17763 fv-az34-210 3.4.7-ea781829.x86_64
Duration: 0hrs 26min 44sec
---
t2/csa_c2c3.csv: 73.87711295363036 [Row 1, MEAN(area)]
t2/csa_pmj.csv: 73.89298021190447 [Row 1, MEAN(area)]
t2/csa_pam50.csv: 34.25734847835911 [Row 39, MEAN(area)]
t2s/csa_gm.csv: 12.487834828856178 [Row 4, MEAN(area)]
t2s/csa_wm.csv: 64.93830702088248 [Row 4, MEAN(area)]
mt/mtr_in_wm.csv: 54.38856944000351 [Row 1, MAP()]
dmri/fa_in_cst.csv: 0.7793405440192693 [Row 1, WA()]
dmri/fa_in_cst.csv: 0.7755611783165834 [Row 2, WA()]
~~~