Detection of Microscopic Glioblastoma Infiltration in Peritumoral Edema Using Interactive Deep Learning With <scp>DTI</scp> Biomarkers: Testing via Stereotactic Biopsy
This study has provided a potential tool, GIAIDF, to identify regions of GBM infiltration within areas of peri-ED based on preoperative MR images.
Authors
- Ji Xiong (ORCID: https://orcid.org/0000-0003-3404-7993)
- A. Daoud (ORCID: https://orcid.org/0000-0002-9498-1940)
- Changxian Shen (ORCID: https://orcid.org/0000-0002-7668-7166)
- Fengping Zhu (ORCID: https://orcid.org/0000-0002-5976-8861)
- Xiangfeng Wang (ORCID: https://orcid.org/0000-0003-1802-4425)
- Zecheng Chen (ORCID: https://orcid.org/0000-0001-7191-852X)
- Yuxin Li (ORCID: https://orcid.org/0000-0003-2107-6744)
- Chao Li (ORCID: https://orcid.org/0000-0002-0734-0011)
- Yan Yan (ORCID: https://orcid.org/0000-0002-5917-1475)
- Bin Hu (ORCID: https://orcid.org/0000-0003-3628-639X)
- Jiaqi Tu (ORCID: https://orcid.org/0009-0006-6957-707X)
- Jianpeng Liu
Institutions
- Xuzhou Medical College (CN)
- University of Dundee (GB)
- University of Cambridge (GB)
- Fudan University (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Faculdade de Ciências Médicas da Santa Casa de São Paulo (BR)
- Huashan Hospital (CN)
- East China Normal University (CN)
Publication Details
- Journal
- Journal of Magnetic Resonance Imaging
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1002/jmri.70058
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Science and Technology Commission of Shanghai Municipality