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Toward reliable thalamic segmentation: an evaluation of automated methods for structural MRI.

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The authors' code

Text · 90 lines · 3.7 KB · CC-BY-NC-SA-4.0

  1. VOXELIZED VERSION of the MOREL ATLAS of the HUMAN THALAMUS
  2. *************************************************************
  3. is a digital image file that represents the 3D anatomy of the thalamus, transformed to the Montreal Neurological Institute 152 anatomical reference space.
  5. Details are found in the following publication:
  7. Andras Jakab, Remi Blanc, Ervin Berenyi and Gábor Székely: Generation of individualized thalamus target maps by using statistical shape models and thalamocortical tractography. AJNR, 33(11) pp. 2110-2116, 2012
  9. and:
  11. Axel Krauth, Remi Blanc, Alejandra Poveda, Daniel Jeanmonod, Anne Morel and Gábor Székely: A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data. Neuroimage, 49(3) pp. 2053-2062, 2010
  13. Any report or publication of results obtained by the use of the Voxelized Version of the Morel Atlas must acknowledge by citing both publications above.
  15. COPYRIGHT NOTICE
  16. ******************
  17. This dataset is released under the Creative Commons Attribution Non Commercial Share Alike 4.0 International License.
  19. Each copy of the Voxelized Version of the Morel Atlas must reproduce the copyright notice:
  20. “© University of Zurich and ETH Zurich, Andras Jakab, Rémi Blanc and Gábor Székely”
  22. DISCLAIMER
  23. ************
  24. The Atlas is provided “as is”. All liabilities are disclaimed. No warranties of any kind are made. Disclaimed warranties include for example:
  25. i. warranty of satisfactory quality and fitness for a particular purpose
  26. ii. warranty of accuracy of results, of the quality and performance of the Atlas
  27. iii. warranty of noninfringement of the intellectual property rights of third parties.
  29. COPYRIGHT NOTICE to the "MNI 152 TEMPLATE"
  30. **********************************
  31. Copyright (C) 1993–2009 Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University. Permission to use, copy, modify, and distribute the "MNI 152 TEMPLATE" and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies. The authors and McGill University make no representations about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. The authors are not responsible for any data loss, equipment damage, property loss, or injury to subjects or patients resulting from the use or misuse of this software package.
  33. Please cite this publicaiton when using the template image:
  34. G. Grabner, A. L. Janke, M. M. Budge, D. Smith, J. Pruessner, and D. L. Collins, “Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults”, Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, vol. 9, pp. 58–66, 2006. https://dx.doi.org/10.1007/11866763_8
  36. FILES
  37. *******
  39. Each atlas file defines a NIFTY GZIPPED image of a particular thalamic sub-structure.
  41. The Atlas is composed of the following files, stored separately for the left and right hemispheres, and in 1mm and 0.5mm isotropic voxel dimensions (166 .nii.gz files):
  43. AD.nii.gz
  44. AM.nii.gz
  45. AV.nii.gz
  46. CeM.nii.gz
  47. CL.nii.gz
  48. CM.nii.gz
  49. global.nii.gz
  50. Hb.nii.gz
  51. LD.nii.gz
  52. LGN.nii.gz
  53. LGNmc.nii.gz
  54. LGNpc.nii.gz
  55. Li.nii.gz
  56. LP.nii.gz
  57. MAX_VOLUME.nii.gz
  58. MDmc.nii.gz
  59. MDpc.nii.gz
  60. MGN.nii.gz
  61. mtt.nii.gz
  62. MV.nii.gz
  63. Pf.nii.gz
  64. Po.nii.gz
  65. PuA.nii.gz
  66. PuI.nii.gz
  67. PuL.nii.gz
  68. PuM.nii.gz
  69. Pv.nii.gz
  70. RN.nii.gz
  71. SG.nii.gz
  72. sPf.nii.gz
  73. STh.nii.gz
  74. thalamus_body.nii.gz
  75. VAmc.nii.gz
  76. VApc.nii.gz
  77. VLa.nii.gz
  78. VLp.nii.gz
  79. VLpd.nii.gz
  80. VLpv.nii.gz
  81. VM.nii.gz
  82. VPI.nii.gz
  83. VPLa.nii.gz
  84. VPLp.nii.gz
  85. VPM.nii.gz
  87. MNI152_T1_0.5mm.nii.gz
  88. MNI152_T1_1mm.nii.gz

Readme.txt, under CC-BY-NC-SA-4.0 · at the source

Overview

Authors: Georgios P. D. Argyropoulos1,2, Christopher R. Butler1,3,4, Manojkumar Saranathan5
ORCID iDs: Georgios P. D. Argyropoulos, Christopher R. Butler, Manojkumar Saranathan
  1. Memory Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford,Oxford, UK
  2. Division of Psychology, Faculty of Natural Sciences, University of Stirling,Stirling, FK9 4LA UK
  3. Department of Brain Sciences, Imperial College London,London, W12 0NN UK
  4. Departamento de Neurología, Pontificia Universidad Católica de Chile,Avda. Libertador Bernando O’Higgins 340, Santiago, Chile
  5. Department of Radiology, University of Massachusetts Chan Medical School,Worcester, MA USA
Institutions: University of Oxford (United Kingdom); University of Stirling (United Kingdom); Imperial College London (United Kingdom); Pontificia Universidad Católica de Chile (Chile); University of Massachusetts Chan Medical School (United States)
Journal: Brain structure & function, volume 231, issue 7, article 102
Dates: received 10 April 2026; accepted 7 July 2026; published online 18 July 2026; in print 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1007/s00429-026-03163-z · PMID 42470458 · PMCID PMC13380577 · OpenAlex W7169657665
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: structural MRI / diffusion (modality), human (organism), methods / tools (subfield)
Methods: Connectivity, Statistics, Machine learning, Spectral & time-frequency, fMRI & imaging
Keywords: Thalamus, Segmentation, THOMAS, HIPS-THOMAS, FreeSurfer, MRI
MeSH: Image Processing, Computer-Assisted*, Magnetic Resonance Imaging*, Neuroimaging*, Thalamus*, Adult, Atlases as Topic, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Middle Aged (* major topic)
Topic: Epilepsy research and treatment (Psychiatry and Mental health, Medicine), according to OpenAlex
Funding: UK Medical Research Council (MR/K010395/1); U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB) (R01 award EB032674)
Citations: not cited yet (Europe PMC); 55 references in the paper

Abstract

Automated thalamic nuclear segmentation has contributed towards a shift in neuroimaging analyses, from treating the thalamus as a homogeneous, passive relay, to a set of individual nuclei, embedded within distinct brain-wide circuits. However, many studies continue to widely rely on FreeSurfer’s segmentation of T1-weighted structural MRIs, despite their poor intrathalamic nuclear contrast. Meanwhile, a convolutional neural network tool has been developed for FreeSurfer, using information from both diffusion and T1-weighted MRIs. Another popular thalamic nuclear segmentation technique is HIPS-THOMAS, a multi-atlas-based method that leverages white-matter-like contrast synthesized from T1-weighted MRIs. However, comparisons amongst methods remain scant, and the thalamic atlases against which these methods have been assessed have their own limitations. These issues may compromise the quality of cross-species comparisons, structural and functional connectivity studies in health and disease, as well as the efficacy of neuromodulatory interventions targeting the thalamus. Here, we report, for the first time, comparisons amongst HIPS-THOMAS, the standard FreeSurfer segmentation, and its more recent development, against two thalamic atlases. We used two cohorts of healthy adults, and one cohort of patients in the chronic phase of autoimmune limbic encephalitis. In healthy adults, HIPS-THOMAS surpassed, not only the standard FreeSurfer segmentation, but also its more recent, diffusion-based update. The improvements made with the latter were limited to a few nuclei. Finally, the standard FreeSurfer method underperformed in distinguishing between patients and healthy controls based on the affected anteroventral and pulvinar nuclei. We provide recommendations on automated segmentation methods of the human thalamus using structural brain imaging.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s00429-026-03163-z.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above.

Zenodo 13918589

License: CC-BY-NC-SA-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
1 file
At the source: zenodo.org/records/13918589

arnaudletroter/7TAMIBrain

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: aa12172b7793c14f73619a1e88ca2c3e400e6b78, 31 May 2023
Size: 7 files
Software Heritage: not archived
Found in: “Data availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
2 files
At the source: github.com/arnaudletroter/7TAMIBrain

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

Demographic and volumetric data are publicly available on https://osf.io/8bp64/. Bash, Matlab, and R scripts are also available there. HCP35 (MGH HCP Adult Diffusion Dataset ID: “MGH_DIFF”): https://db.humanconnectome.org/data/projects/MGH_DIFF. Data collection and sharing for this project was provided by the Human Connectome Project (HCP; Principal Investigators: Bruce Rosen, M.D., Ph.D., Martinos Center at Massachusetts General Hospital; Arthur W. Toga, Ph.D., University of Southern California; Van J. Weeden, MD, Martinos Center at Massachusetts General Hospital). HCP funding was provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS). HCP data are disseminated by the Laboratory of Neuro Imaging at the University of Southern California. HCP is the result of efforts of co-investigators from the University of Southern California, Martinos Center for Biomedical Imaging at Massachusetts General Hospital (MGH), Washington University, and the University of Minnesota. FS-T1: FreeSurfer segmentation was Conducted following the instructions provided in https://freesurfer.net/fswiki/ThalamicNuclei). HIPS-THOMAS: Details for running HIPS-THOMAS using Docker are available on Github (HIPS-THOMAS https://github.com/thalamicseg/hipsthomasdocker); the Docker images are available on Docker Hub (https://hub.docker.com/u/anagrammarian). FS-DTI: details on its use can be found in https://surfer.nmr.mgh.harvard.edu/fswiki/ThalamicNucleiDTI. We used the updated model (`thalseg_1.1.h5`) made available https://ftp.nmr.mgh.harvard.edu/pub/dist/freesurfer/thalseg/ThalsegPatch_1.1.tgz) (validated against additional datasets) which we called with the “—model” option. Improvements to the segmentation script were downloaded from https://github.com/freesurfer/freesurfer/blob/dev/mri_segment_thalamic_nuclei_dti_cnn/mri_segment_thalamic_nuclei_dti_cnn and were used to replace the release version, in order to prevent occurrences of false positive thalamic segmentations; “Morel”: Krauth-Morel atlas, available on https://zenodo.org/records/13918589; “Marseille”: 7TAMIbrainDGN, available on https://github.com/arnaudletroter/7TAMIBrain.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 2, 28 September 2026

  • Publisher: n/a → Springer Science+Business Media

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 6 keywords, 11 MeSH terms, 2 funders, 51 references.

Cite

This paper

Argyropoulos, G. P. D., Butler, C. R., & Saranathan, M. (2026). Toward reliable thalamic segmentation: an evaluation of automated methods for structural MRI. Brain structure & function, 231(7), 102. https://doi.org/10.1007/s00429-026-03163-z

BibTeX

@article{argyropoulos2026toward,
author = {Argyropoulos, Georgios P. D. and Butler, Christopher R. and Saranathan, Manojkumar},
title = {{Toward reliable thalamic segmentation: an evaluation of automated methods for structural MRI}},
journal = {Brain structure \& function},
year = {2026},
month = jul,
volume = {231},
number = {7},
pages = {102},
publisher = {Springer Science+Business Media},
issn = {1863-2653},
doi = {10.1007/s00429-026-03163-z},
url = {https://doi.org/10.1007/s00429-026-03163-z},
pmid = {42470458},
pmcid = {PMC13380577}
}

RIS

TY - JOUR
AU - Argyropoulos, Georgios P. D.
AU - Butler, Christopher R.
AU - Saranathan, Manojkumar
TI - Toward reliable thalamic segmentation: an evaluation of automated methods for structural MRI
T2 - Brain structure & function
J2 - Brain Struct Funct
PY - 2026
DA - 2026/07/18
VL - 231
IS - 7
SP - 102
SN - 1863-2653
PB - Springer Science+Business Media
DO - 10.1007/s00429-026-03163-z
UR - https://doi.org/10.1007/s00429-026-03163-z
LA - en
ER -

CSL-JSON

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