Attention Mechanisms in U-Net Variants for Brain MRI Segmentation: A Narrative Review of Spatial, Channel, and Transformer-Based Approaches

Ali khodadadi, Mohammad Shakoor

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DOI: 10.61882/ist.202502.09.03
Published: 9
Container: InfoScience Trends
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.61882/ist.202502.09.03,
  title = {Attention Mechanisms in U-Net Variants for Brain MRI Segmentation: A Narrative Review of Spatial, Channel, and Transformer-Based Approaches},
  author = {Ali khodadadi and Mohammad Shakoor},
  year = {2025},
  journal = {InfoScience Trends},
  doi = {10.61882/ist.202502.09.03},
  url = {https://doi.org/10.61882/ist.202502.09.03}
}

RIS

TY  - JOUR
TI  - Attention Mechanisms in U-Net Variants for Brain MRI Segmentation: A Narrative Review of Spatial, Channel, and Transformer-Based Approaches
AU  - Ali khodadadi
AU  - Mohammad Shakoor
PY  - 2025
JO  - InfoScience Trends
DO  - 10.61882/ist.202502.09.03
UR  - https://doi.org/10.61882/ist.202502.09.03
ER  -

APA

khodadadi, A., & Shakoor, M. (2025). Attention Mechanisms in U-Net Variants for Brain MRI Segmentation: A Narrative Review of Spatial, Channel, and Transformer-Based Approaches. InfoScience Trends. https://doi.org/10.61882/ist.202502.09.03

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doaj · retrieved 2026-09-25T03:53:45.221Z