Generalizable multi-modal medical image segmentation model using Multi-head Gated Cross Attention fusion Encoder-based adaptive Trans-Mobile-Unet++ with consistency loss function
- DOI
- 10.1016/j.compbiolchem.2026.109366
- Published
- 2027-02
- Container
- Computational Biology and Chemistry
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.compbiolchem.2026.109366,
title = {Generalizable multi-modal medical image segmentation model using Multi-head Gated Cross Attention fusion Encoder-based adaptive Trans-Mobile-Unet++ with consistency loss function},
author = {Chinnamgari Neeraja and G. Umamaheswara Reddy and Gowri Thumbur},
year = {2027},
journal = {Computational Biology and Chemistry},
doi = {10.1016/j.compbiolchem.2026.109366},
url = {https://doi.org/10.1016/j.compbiolchem.2026.109366}
}RIS
TY - JOUR TI - Generalizable multi-modal medical image segmentation model using Multi-head Gated Cross Attention fusion Encoder-based adaptive Trans-Mobile-Unet++ with consistency loss function AU - Chinnamgari Neeraja AU - G. Umamaheswara Reddy AU - Gowri Thumbur PY - 2027 JO - Computational Biology and Chemistry DO - 10.1016/j.compbiolchem.2026.109366 UR - https://doi.org/10.1016/j.compbiolchem.2026.109366 ER -
APA
Neeraja, C., Reddy, G. U., & Thumbur, G. (2027). Generalizable multi-modal medical image segmentation model using Multi-head Gated Cross Attention fusion Encoder-based adaptive Trans-Mobile-Unet++ with consistency loss function. Computational Biology and Chemistry. https://doi.org/10.1016/j.compbiolchem.2026.109366
Source records
- crossref · retrieved 2026-09-25T12:11:43.150Z