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High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture.

Overview

Authors: D Ramana Kumar1, P Vamsheedhar Reddy2, Hafeena Mohammad3, Guda Madhu4, Sangamitra B K5, M Narender6, A Mahendar5
ORCID iDs: M Narender
  1. Department of Computer Science and Engineering, School of Engineering, Anurag University, Hyderabad, Telangana India
  2. Department of CSE AI&ML, Keshav Memorial Engineering College, Hyderabad, Telangana India
  3. Department of CSE (Data Science), Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh India
  4. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad, Telangana 500043 India
  5. Department of CSE (Data Science), CMR Technical Campus, Hyderabad, Telangana India
  6. Department of Computer Science and Engineering, TKR College of Engineering and Technology, Hyderabad, Telangana India
Institutions: Prasad V. Potluri Siddhartha Institute of Technology (India); Koneru Lakshmaiah Education Foundation (India)
Journal: Scientific reports, volume 16, issue 1, article 20154
Dates: received 21 December 2025; accepted 20 April 2026; published online 14 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-50240-8 · PMID 42135350 · PMCID PMC13324711 · OpenAlex W7161148832
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: structural MRI / diffusion (modality), human (organism), other condition (population), methods / tools (subfield)
Methods: Connectivity, Machine learning, fMRI & imaging
Keywords: Brain tumor segmentation, Faster R-CNN, Switchable normalization, Multi-modal MRI, Deep learning, Region proposal network, Dice similarity coefficient, Medical image analysis, Cancer, Computational biology and bioinformatics, Engineering, Mathematics and computing
MeSH: Brain Neoplasms*, Image Processing, Computer-Assisted*, Magnetic Resonance Imaging*, Algorithms, Convolutional Neural Networks, Humans, Neural Networks, Computer (* major topic)
Topic: Advanced Neural Network Applications (Computer Vision and Pattern Recognition, Computer Science), according to OpenAlex
Citations: not cited yet (Europe PMC); 31 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

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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:

  • no repository, dataset or request procedure was recognized in it

Read it in the paper: doi.org/10.1038/s41598-026-50240-8.

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, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 12 keywords, 7 MeSH terms, 16 references.

Cite

This paper

Kumar, D. R., Reddy, P. V., Mohammad, H., Madhu, G., K, S. B., Narender, M., & Mahendar, A. (2026). High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture. Scientific reports, 16(1), 20154. https://doi.org/10.1038/s41598-026-50240-8

BibTeX

@article{kumar2026high,
author = {Kumar, D Ramana and Reddy, P Vamsheedhar and Mohammad, Hafeena and Madhu, Guda and K, Sangamitra B and Narender, M and Mahendar, A},
title = {{High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture}},
journal = {Scientific reports},
year = {2026},
month = may,
volume = {16},
number = {1},
pages = {20154},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-50240-8},
url = {https://doi.org/10.1038/s41598-026-50240-8},
pmid = {42135350},
pmcid = {PMC13324711}
}

RIS

TY - JOUR
AU - Kumar, D Ramana
AU - Reddy, P Vamsheedhar
AU - Mohammad, Hafeena
AU - Madhu, Guda
AU - K, Sangamitra B
AU - Narender, M
AU - Mahendar, A
TI - High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/05/14
VL - 16
IS - 1
SP - 20154
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-50240-8
UR - https://doi.org/10.1038/s41598-026-50240-8
LA - en
ER -

CSL-JSON

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"language": "en",
"issued": {
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