Multiple attention channels aggregated network for multimodal medical image fusion
The proposed multiple attention channels aggregated network (MACAN) can effectively retain the complementary information from source images. The evaluation of MACAN through medical image fusion and segmentation experiments on public datasets demonstrated its superiority over the state-of-the-art methods, both in terms of visual quality and objective metrics. Our code is available at https://github.com/JasonWong30/MACAN.
Authors
- Yanxiong Wu (ORCID: https://orcid.org/0000-0003-3592-7175)
- Xiaosong Li (ORCID: https://orcid.org/0000-0003-4672-1527)
- Tao Ye (ORCID: https://orcid.org/0000-0002-1814-530X)
- Jingxue Huang
- Tianshu Tan
Institutions
- Foshan University (CN)
- Hong Kong University of Science and Technology (HK)
- China University of Mining and Technology (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1002/mp.17607
- Citations
- 7
- Primary Topic
- Advanced Image Fusion Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.24