TransCeption: Enhancing medical image segmentation with an inception-like transformer design for efficient feature fusion

Reza Azad, Yiwei Jia, Ehsan Khodapanah Aghdam, Julien Cohen-Adad and Dorit Merhof

Article (2025)

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Department:	Department of Electrical Engineering Institut de génie biomédical
Research Center:	NeuroPoly - Laboratoire de Recherche en Neuroimagerie
Funders:	German Research Foundation
Grant number:	455548460
PolyPublie URL:	https://publications.polymtl.ca/66624/
Journal Title:	Computational Visual Media
Publisher:	Springer Nature
DOI:	10.26599/cvm.2025.9450407
Official URL:	https://doi.org/10.26599/cvm.2025.9450407
Date Deposited:	22 Jul 2025 15:43
Last Modified:	22 Jul 2025 15:44

Cite in APA 7:	Azad, R., Jia, Y., Khodapanah Aghdam, E., Cohen-Adad, J., & Merhof, D. (2025). TransCeption: Enhancing medical image segmentation with an inception-like transformer design for efficient feature fusion. Computational Visual Media, 17 pages. https://doi.org/10.26599/cvm.2025.9450407
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