Releases · spinalcordtoolbox/spinalcordtoolbox

Caution

Version 7.2 of SCT has been yanked due to a signfiicant issue with the sct_process_segmentation script:

Large RAM usage and very slow processing for sct_process_segmentation in v7.2 - #5120

For now, we recommend uninstalling v7.2 and instead installing v7.1 for any processing that requires sct_process_segmentation. For transparency, the v7.2 source code has been preserved here.

The SCT development team will be issuing a v7.2.1 release shortly once the issue has been fixed.

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 -discfile to sct_process_segmentation to allow for determining VertLevel using projected disc labels. View pull request
Enhancement: Update lesion_ms DeepSeg model from r20241101 to r20250626 (ESMRMB 2025). View pull request
Enhancement: Use centerline of -vertfile in sct_extract_metric for more accurate mapping of VertLevel to 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_transfo when applying -initwarp during 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()]
~~~

Important

Initial release: 2025-04-24
Last updated: 2025-05-08 (⚠️ New! ⚠️: QC Report hotfix.)

Notable changes include:

Feature: Reworked sct_deepseg syntax, interface, and model names. View pull request
- Add lesion_ms_axial_t2 model to sct_deepseg for MS lesion/SC segmentation of axial T2 images. View pull request
- Add graymatter model to sct_deepseg for contrast-agnostic segmentation of the gray matter. View pull request
- Update spinalcord contrast-agnostic model to retrain from scratch using nnUNetv2 framework. View pull request
- Update rootlets T2 model to now segment MP2RAGE images as well. View pull request
Feature Add new CLI tool (sct_detect_compression) to predict compression probability. View pull request
Feature: Add -lrootlet argument to sct_register_to_template to 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 spinalcord segmentation 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()]
~~~

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_deepseg to 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()]

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.txt for sct_analyze_lesion -f. View pull request
Feature: Add slicewise analysis for sct_analyze_lesion -f. View pull request
Feature: Track sct_deepseg model provenance with source.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_deepseg model to v2.4 (now improved for lumbar t2w + PSIR/STIR images). View pull request
Enhancement: Update SCI sct_deepseg model to SCIsegV2. View pull request
Enhancement: Improve sct_deepseg rootlets seg QC report by improving the cropping, centering, and colormap. View pull request
Enhancement: Use LazyLoader class 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()]
~~~

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-agnostic SC segmentation model (sct_deepseg) to the latest version (v2.3). View pull request
Enhancement: Switch to using mean magnitude for output moco_params.tsv file 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()]
~~~

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.gz file. 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()]
~~~

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_compression View 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 -s functionality from sct_warp_template and 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 .csv saving in sct_compute_compression to 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()]
~~~

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_sct to 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 -histo option to sct_warp_template to warp the newly-added PAM50 histology files. View pull request
Feature: Add new sagittal mosaic option for sct_deepseg_lesion QC report. View pull request
Feature: Add support for model ensembles to sct_deepseg and use it for mp2rage_lesion model. View pull request
Feature: Add new -project-centerline option to sct_label_utils to project an image on the spinal cord centerline. View pull request
Feature: Add new -centerline-soft option to sct_get_centerline to output a non-binary "soft" centerline. View pull request
Bugfix: Ensure that qform/sform codes are preserved when generating sct_deepseg_sc segmentation. 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()]
~~~

Important

Initial release: 2023-01-23
Last updated: 2025-02-25 (⚠️ New! ⚠️: Anaconda licensing changes)

Notable changes include:

Feature: sct_image: Add new -stitch option for combining sequential image scans. View pull request
Feature: sct_run_batch: Add new -ignore-ses option to prioritize sub- directories over ses- subdirectories. View pull request
Feature: sct_process_segmentation: For the -perslice option, begin outputting the DistancePMJ metric. View pull request
Enhancement: Add readability fixes for QC reports (sagittal view scaling, label text, label colormaps). View pull request
Enhancement: image.py: Update header dtype property on save/load to match the datatype of the data array. View pull request
Bugfix: sct_run_batch: Modify -include-list and -exclude-list to check against parts of a directory, too. View pull request
Bugfix: sct_run_batch: Allow path_output parameter to start with ~. View pull request
Installation: Upgrade SCT from Python 3.7 to Python 3.8. View pull request
Documentation: Emphasize references to PMJ method by Bédard and Cohen-Adad. View pull request

Full release notes and Changelog

Results of batch_processing.sh on Ubuntu 20.04

 ~~~
Version:         git-master-71e199dc14156e895880bc8e74de8409a2d238c8
Ran on:          Linux fv-az259-426 5.15.0-1023-azure
Duration:        0hrs 23min 13sec
---
t2/csa_c2c3.csv:     73.87711295363036  [Row 1, MEAN(area)]
t2/csa_pmj.csv:      73.89298021190447  [Row 1, 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:    54.37973940532884  [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-71e199dc14156e895880bc8e74de8409a2d238c8
Ran on:          Darwin Mac-1669763228410.local 20.6.0
Duration:        0hrs 28min 36sec
---
t2/csa_c2c3.csv:     73.87711295363036  [Row 1, MEAN(area)]
t2/csa_pmj.csv:      73.89298021190447  [Row 1, 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:    54.424258247179175 [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-71e199dc14156e895880bc8e74de8409a2d238c8
Ran on:          MINGW64_NT-10.0-17763 fv-az30-853 3.3.6-341.x86_64
Duration:        0hrs 24min 52sec
---
batch_processing.sh: line 267: ./python/envs/venv_sct/bin/python: No such file or directory
t2/csa_c2c3.csv:     73.87711295363036  [Row 1, MEAN(area)]
t2/csa_pmj.csv:      73.89298021190447  [Row 1, 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:    54.37973940532884  [Row 1, MAP()]
dmri/fa_in_cst.csv:  0.7793405440192693 [Row 1, WA()]
dmri/fa_in_cst.csv:  0.7755611783165834 [Row 2, WA()]
~~~

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Releases: spinalcordtoolbox/spinalcordtoolbox

7.2

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7.1

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7.0

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6.5

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6.4

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6.3

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6.2

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6.1

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SCT v6.0

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SCT v5.8

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