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Attention U-Net with differential privacy in federated learning framework for brain stroke lesion segmentation.

Overview

Authors: M. Adhi Siva1, Chiranji Lal Chowdhary1
  1. School of Computer Science Engineering and Information Systems, Vellore Institute of Technology,Vellore, Tamil Nadu 632014 India
Institutions: Vellore Institute of Technology University (India)
Journal: Scientific reports, volume 16, issue 1, article 25583
Dates: received 2 January 2026; accepted 14 May 2026; published online 4 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-53829-1 · PMID 42243272 · PMCID PMC13478167 · OpenAlex W7163589854
Open access: gold, a free copy (OpenAlex)
Status: dead link
Categories: human (organism), stroke (population), methods / tools (subfield)
Methods: Connectivity, Preprocessing, Machine learning, Smoothing, state filtering, decompositions
Keywords: Federated learning, Brain stroke segmentation, Fed-AttUNet-DP, Differential privacy, Attention U-Net, Medical image analysis, secure aggregation, Non-IID data, Computational biology and bioinformatics, Engineering, Health care, Mathematics and computing
MeSH: Neuroimaging*, Stroke*, Algorithms, Brain, Federated Learning, Humans, Image Processing, Computer-Assisted, Privacy (* major topic)
Topic: Privacy-Preserving Technologies in Data (Artificial Intelligence, Computer Science), according to OpenAlex
Funding: Vellore Institute of Technology, Vellore
Citations: not cited yet (Europe PMC); 44 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.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

adhisivasys1984/fl-attentionunet-dp

License: none: the authors keep all their rights
State: the link is dead, verified on 27 September 2026
Evidence: found in the paper
Software Heritage: not archived
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 is dead
  • 27 September 2026: the link is dead
At the source: github.com/adhisivasys1984/FL-AttentionUNet-DP/blob/main/FlAttUNetDP.ipynb

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.

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

Code and data availability statement

The paper has a code and 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/10.1038/s41598-026-53829-1.

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 12 keywords, 8 MeSH terms, 1 funder, 18 references.

Cite

This paper

Adhi Siva, M., & Chowdhary, C. L. (2026). Attention U-Net with differential privacy in federated learning framework for brain stroke lesion segmentation. Scientific reports, 16(1), 25583. https://doi.org/10.1038/s41598-026-53829-1

BibTeX

@article{adhisiva2026attention,
author = {Adhi Siva, M. and Chowdhary, Chiranji Lal},
title = {{Attention U-Net with differential privacy in federated learning framework for brain stroke lesion segmentation}},
journal = {Scientific reports},
year = {2026},
month = jun,
volume = {16},
number = {1},
pages = {25583},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-53829-1},
url = {https://doi.org/10.1038/s41598-026-53829-1},
pmid = {42243272},
pmcid = {PMC13478167}
}

RIS

TY - JOUR
AU - Adhi Siva, M.
AU - Chowdhary, Chiranji Lal
TI - Attention U-Net with differential privacy in federated learning framework for brain stroke lesion segmentation
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/06/04
VL - 16
IS - 1
SP - 25583
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-53829-1
UR - https://doi.org/10.1038/s41598-026-53829-1
LA - en
ER -

CSL-JSON

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The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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[10] doi:10.1038/s41598-026-55847-5
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