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Synthetic cervical spine radiographs: expert validation and transfer learning for low-data settings.

Code ↔ Paper

The paper beside its authors' code: matches between them have not been computed for this paper yet.

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Shell · 21 lines · 549 B · no license

  1. #!/bin/bash
  3. python src/ddpm.py \
  4. --model_dim 64 \
  5. --channels 1 \
  6. --dim_mults 1 2 4 8 \
  7. --flash_attn \
  8. --image_size 256 \
  9. --timesteps 1000 \
  10. --sampling_timesteps 500 \
  11. --dataset_path "/acfs-home/abh4006/serag_AI_lab/users/abh4006/scripts/ssl_synth/Syn-Med/tmp_ultra_sound_dt" \
  12. --results_folder "./results" \
  13. --train_batch_size 8 \
  14. --train_lr 5e-5 \
  15. --train_num_steps 300000 \
  16. --gradient_accumulate_every 2 \
  17. --ema_decay 0.995 \
  18. --amp \
  19. --save_and_sample_every 50000 \
  20. --convert_image_to "L" \
  21. --sample_outdir ""

pretrain_ddpm.sh at commit 9736dc5, no license · at the source

Overview

Authors: Austin A Barr1, Brij S Karmur2,3, Anthony J Winder4, Eddie Guo5, John T Lysack4, James N Scott4, William F Morrish4, Muneer Eesa4, Morgan Willson4, David W Cadotte2, Michael M H Yang2, Ian Y M Chan6, Sanju Lama2,3, Garnette R Sutherland2,3
  1. Cumming School of Medicine, University of Calgary, Calgary, AB Canada
  2. Section of Neurosurgery, Department of Clinical Neurosciences, University of Calgary, Calgary, AB Canada
  3. Project neuroArm, Department of Clinical Sciences, University of Calgary, Calgary, AB Canada
  4. Department of Radiology, University of Calgary, Calgary, AB Canada
  5. Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON Canada
  6. Department of Medical Imaging, University of Toronto, Toronto, ON Canada
Institutions: University of Calgary (Canada); University of Toronto (Canada)
Journal: BMC medical informatics and decision making, volume 26, issue 1, article 172
Dates: received 13 December 2025; accepted 3 April 2026; published online 11 April 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1186/s12911-026-03479-0 · PMID 41965677 · PMCID PMC13185266 · OpenAlex W7153519645
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), methods / tools (subfield)
Methods: Statistics, Machine learning
Keywords: Synthetic data, Diffusion models, Neuroimaging, Neurosurgery, Spine, Machine learning, Transfer learning, Data sharing
MeSH: Cervical Vertebrae*, Machine Learning*, Neuroimaging*, Radiography*, Humans, Transfer Machine Learning (* major topic)
Topic: Medical Imaging and Analysis (Biomedical Engineering, Engineering), according to OpenAlex
Citations: not cited yet (Europe PMC); 38 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

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

serag-ai/I-SynMed

License: none: the authors keep all their rights
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Commit: 9736dc54b62970dbc584034265b5e9badb4acbd1, 26 May 2026
Languages: Shell (3), Python (2)
Size: 7 files, 5 scripts
Software Heritage: not archived
Found in: the text, “DDPM implementation and training”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Pillow (1 file), PyTorch (1 file)
Availability: 1 check, the latest on 29 September 2026: the link answers
  • 29 September 2026: the link answers
6 files
At the source: github.com/serag-ai/I-SynMed

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:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 5 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 statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1186/s12911-026-03479-0.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 14 authors, 8 keywords, 6 MeSH terms, 28 references.

Cite

This paper

Barr, A. A., Karmur, B. S., Winder, A. J., Guo, E., Lysack, J. T., Scott, J. N., Morrish, W. F., Eesa, M., Willson, M., Cadotte, D. W., Yang, M. M. H., Chan, I. Y. M., Lama, S., & Sutherland, G. R. (2026). Synthetic cervical spine radiographs: expert validation and transfer learning for low-data settings. BMC medical informatics and decision making, 26(1), 172. https://doi.org/10.1186/s12911-026-03479-0

BibTeX

@article{barr2026synthetic,
author = {Barr, Austin A and Karmur, Brij S and Winder, Anthony J and Guo, Eddie and Lysack, John T and Scott, James N and Morrish, William F and Eesa, Muneer and Willson, Morgan and Cadotte, David W and Yang, Michael M H and Chan, Ian Y M and Lama, Sanju and Sutherland, Garnette R},
title = {{Synthetic cervical spine radiographs: expert validation and transfer learning for low-data settings}},
journal = {BMC medical informatics and decision making},
year = {2026},
month = apr,
volume = {26},
number = {1},
pages = {172},
publisher = {BMC},
issn = {1472-6947},
doi = {10.1186/s12911-026-03479-0},
url = {https://doi.org/10.1186/s12911-026-03479-0},
pmid = {41965677},
pmcid = {PMC13185266}
}

RIS

TY - JOUR
AU - Barr, Austin A
AU - Karmur, Brij S
AU - Winder, Anthony J
AU - Guo, Eddie
AU - Lysack, John T
AU - Scott, James N
AU - Morrish, William F
AU - Eesa, Muneer
AU - Willson, Morgan
AU - Cadotte, David W
AU - Yang, Michael M H
AU - Chan, Ian Y M
AU - Lama, Sanju
AU - Sutherland, Garnette R
TI - Synthetic cervical spine radiographs: expert validation and transfer learning for low-data settings
T2 - BMC medical informatics and decision making
J2 - BMC Med Inform Decis Mak
PY - 2026
DA - 2026/04/11
VL - 26
IS - 1
SP - 172
SN - 1472-6947
PB - BMC
DO - 10.1186/s12911-026-03479-0
UR - https://doi.org/10.1186/s12911-026-03479-0
LA - en
ER -

CSL-JSON

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"id": "10.1186/s12911-026-03479-0",
"type": "article-journal",
"title": "Synthetic cervical spine radiographs: expert validation and transfer learning for low-data settings",
"container-title": "BMC medical informatics and decision making",
"author": [
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"family": "Barr",
"given": "Austin A"
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{
"family": "Guo",
"given": "Eddie"
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{
"family": "Lysack",
"given": "John T"
},
{
"family": "Scott",
"given": "James N"
},
{
"family": "Morrish",
"given": "William F"
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{
"family": "Eesa",
"given": "Muneer"
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{
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{
"family": "Cadotte",
"given": "David W"
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{
"family": "Yang",
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{
"family": "Chan",
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{
"family": "Lama",
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{
"family": "Sutherland",
"given": "Garnette R"
}
],
"container-title-short": "BMC Med Inform Decis Mak",
"volume": "26",
"issue": "1",
"page": "172",
"DOI": "10.1186/s12911-026-03479-0",
"PMID": "41965677",
"PMCID": "PMC13185266",
"ISSN": "1472-6947",
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"URL": "https://doi.org/10.1186/s12911-026-03479-0",
"language": "en",
"issued": {
"date-parts": [
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2026,
4,
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]
}
}

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