A densely connected deep learning method for joint brain tumor segmentation and classification
- DOI
- 10.1016/j.health.2026.100494
- Published
- 12
- Container
- Healthcare Analytics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.health.2026.100494,
title = {A densely connected deep learning method for joint brain tumor segmentation and classification},
author = {Mukta Roy and Moinul Hossain and Munshaibur Rahman Mahin and Zikrul Shariar Ayon and Jia Uddin and Debasish Ghose},
year = {2026},
journal = {Healthcare Analytics},
doi = {10.1016/j.health.2026.100494},
url = {https://doi.org/10.1016/j.health.2026.100494}
}RIS
TY - JOUR TI - A densely connected deep learning method for joint brain tumor segmentation and classification AU - Mukta Roy AU - Moinul Hossain AU - Munshaibur Rahman Mahin AU - Zikrul Shariar Ayon AU - Jia Uddin AU - Debasish Ghose PY - 2026 JO - Healthcare Analytics DO - 10.1016/j.health.2026.100494 UR - https://doi.org/10.1016/j.health.2026.100494 ER -
APA
Roy, M., Hossain, M., Mahin, M. R., Ayon, Z. S., Uddin, J., & Ghose, D. (2026). A densely connected deep learning method for joint brain tumor segmentation and classification. Healthcare Analytics. https://doi.org/10.1016/j.health.2026.100494
Source records
- doaj · retrieved 2026-11-10T16:38:15.429Z