Classifications of meningioma brain images using the novel Convolutional Fuzzy C Means (CFCM) architecture and performance analysis of hardware incorporated tumor segmentation module.
- DOI
- 10.1080/0954898x.2025.2491537
- Published
- 2025 Apr 24
- Container
- Network (Bristol, England)
- Publisher
- Not recorded
- Open access
- no
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1080/0954898x.2025.2491537,
title = {Classifications of meningioma brain images using the novel Convolutional Fuzzy C Means (CFCM) architecture and performance analysis of hardware incorporated tumor segmentation module.},
author = {Jayaram K and Kumarganesh S and Immanuvel A and Ganesh C},
year = {2025},
journal = {Network (Bristol, England)},
doi = {10.1080/0954898x.2025.2491537},
url = {https://doi.org/10.1080/0954898x.2025.2491537}
}RIS
TY - JOUR TI - Classifications of meningioma brain images using the novel Convolutional Fuzzy C Means (CFCM) architecture and performance analysis of hardware incorporated tumor segmentation module. AU - Jayaram K AU - Kumarganesh S AU - Immanuvel A AU - Ganesh C PY - 2025 JO - Network (Bristol, England) DO - 10.1080/0954898x.2025.2491537 UR - https://doi.org/10.1080/0954898x.2025.2491537 ER -
APA
K, J., S, K., A, I., & C, G. (2025). Classifications of meningioma brain images using the novel Convolutional Fuzzy C Means (CFCM) architecture and performance analysis of hardware incorporated tumor segmentation module.. Network (Bristol, England). https://doi.org/10.1080/0954898x.2025.2491537
Source records
- pubmed · retrieved 2026-09-26T02:33:43.169Z
- europe-pmc · retrieved 2026-09-26T02:33:43.178Z