A 3D hierarchical cross‐modality interaction network using transformers and convolutions for brain glioma segmentation in MR images
Our proposed method can accurately and automatically segment glioma regions from multi-parametric MR images, which is beneficial for the quantitative analysis of brain gliomas and helpful for reducing the annotation burden of neuroradiologists.
Authors
- Jiaosong Long
- Yuzhou Zhuang (ORCID: https://orcid.org/0000-0003-4494-3660)
- Chuanbin Ge
- Guangzhi Ma (ORCID: https://orcid.org/0000-0001-5726-1672)
- Wei Fang (ORCID: https://orcid.org/0000-0002-5561-7249)
- Yunfeng Zhu (ORCID: https://orcid.org/0000-0003-2122-3011)
- Hong Liu (ORCID: https://orcid.org/0000-0001-7064-6411)
- Si‐Si Sun
- Enmin Song
- Xu Zhang (ORCID: https://orcid.org/0000-0002-7909-9378)
- Wenyang Chen
Institutions
- United Imaging Healthcare (China) (CN)
- Huazhong University of Science and Technology (CN)
- Hubei University of Technology (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-08-13
- DOI
- https://doi.org/10.1002/mp.17354
- Citations
- 1
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.25