Precise identification of medulloblastoma in MRI images using a convolutional neural network integrated with a self-attention mechanism
InceptentionNet demonstrates robust predictive capabilities and has the potential as a diagnostic assistant tool. In the future, the model should be trained and validated using larger data and multiclass classification should be expanded.
Authors
- Hong Chen (ORCID: https://orcid.org/0000-0002-2793-6461)
- Chenhao Fang
- Xianzhen Chen (ORCID: https://orcid.org/0000-0003-1915-4686)
- Zhaoli Shen
- Chao Li (ORCID: https://orcid.org/0000-0002-0870-3988)
- Shuo Li (ORCID: https://orcid.org/0000-0003-2331-2448)
- Huiqing Liu (ORCID: https://orcid.org/0000-0002-5227-5204)
- Qiang Zhou (ORCID: https://orcid.org/0000-0002-9770-1916)
Institutions
- Tongji University (CN)
- Fujian Medical University (CN)
- Shanghai Jiao Tong University (CN)
- Shanghai Children's Medical Center (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
- Shanghai Tenth People's Hospital (CN)
- Second Affiliated Hospital of Nanjing Medical University (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251351536
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province