Fine-grained Prototype Network for MRI Sequence Classification
The proposed new MRI sequence classification model, SequencesNet, addresses the problem of subtle inter-class differences and significant intraclass variations existing in medical images. The modular design of SequencesNet can be extended to other medical imaging tasks, including but not limited to multimodal image fusion, lesion detection, and disease staging. Future work can be done to decrease the computational complexity and increase the generalization of the model.
Authors
- C. Q. Yuan
- Xibin Jia (ORCID: https://orcid.org/0000-0001-8799-8042)
- Chuanxu Yang (ORCID: https://orcid.org/0000-0003-0884-6943)
- Luo Wang (ORCID: https://orcid.org/0000-0001-7065-2504)
Institutions
- Beijing University of Technology (CN)
Publication Details
- Journal
- Current Medical Imaging Formerly Current Medical Imaging Reviews
- Published
- 2025-08-04
- DOI
- https://doi.org/10.2174/0115734056361649250717162910
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00