Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention
This study underscores the advantages of integrating frequency-domain analysis with optimized attention mechanisms, paving the way for scalable, high-performance medical image segmentation algorithms with broader clinical diagnostic applications.
Authors
- Haoliang Li (ORCID: https://orcid.org/0000-0002-3312-8532)
- Yuqing Miao (ORCID: https://orcid.org/0000-0002-8330-2666)
- Tao Zhang (ORCID: https://orcid.org/0000-0002-8157-7674)
- Shuyi Wang (ORCID: https://orcid.org/0000-0001-8383-8412)
- Yongmin Zhong (ORCID: https://orcid.org/0000-0002-0105-9296)
Institutions
- University of Shanghai for Science and Technology (CN)
Publication Details
- Journal
- Brain Sciences
- Published
- 2025-06-06
- DOI
- https://doi.org/10.3390/brainsci15060613
- Citations
- 2
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 1.68