Lightweight hybrid Mamba2 for unsupervised medical image registration

HybridMorph brings significant performance improvements and lower computational overhead compared to baseline methods, demonstrating the potential of our model in promoting the lightweight design of medical image registration models.

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Publication Details

Journal
Medical Physics
Published
2025-09-01
DOI
https://doi.org/10.1002/mp.18104
Primary Topic
Medical Image Segmentation Techniques
Type
article
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article

Lightweight hybrid Mamba2 for unsupervised medical image registration

Wenkang Chen, Ao‐Bo Xu, Shaofei Shen, Xuejun Zhang
4 links
Medical Physics
Medical Image Segmentation Techniques
article

Lightweight hybrid Mamba2 for unsupervised medical image registration

Wenkang Chen, Ao‐Bo Xu, Shaofei Shen, Xuejun Zhang
article en

Abstract

HybridMorph brings significant performance improvements and lower computational overhead compared to baseline methods, demonstrating the potential of our model in promoting the lightweight design of medical image registration models.

Medical PhysicsVol. 52(9)
Guangxi University (CN), Guangxi Science and Technology Department (CN)
Openalex Percentile: Top 77%
Medical Image Segmentation Techniques
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