Hybrid deep learning approach for early emphysema diagnosis combining fuzzy C-means, TransUNet, and faster mask R-CNN
- DOI
- 10.1038/s41598-026-55142-3
- Published
- 2026-06-04
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-55142-3,
title = {Hybrid deep learning approach for early emphysema diagnosis combining fuzzy C-means, TransUNet, and faster mask R-CNN},
author = {Meenakshi Dharmaraj and Anbarasan Murugesan},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-55142-3},
url = {https://doi.org/10.1038/s41598-026-55142-3}
}RIS
TY - JOUR TI - Hybrid deep learning approach for early emphysema diagnosis combining fuzzy C-means, TransUNet, and faster mask R-CNN AU - Meenakshi Dharmaraj AU - Anbarasan Murugesan PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-55142-3 UR - https://doi.org/10.1038/s41598-026-55142-3 ER -
APA
Dharmaraj, M., & Murugesan, A. (2026). Hybrid deep learning approach for early emphysema diagnosis combining fuzzy C-means, TransUNet, and faster mask R-CNN. Scientific Reports. https://doi.org/10.1038/s41598-026-55142-3
Source records
- crossref · retrieved 2026-09-25T12:53:06.168Z