Deep learning–powered temperature prediction for optimizing transcranial MR-guided focused ultrasound treatment
These results showcase the exciting potential of Fust-Net for achieving precise temperature control during MRgFUS treatment, opening new doors for enhanced precision and safety in clinical applications.
Authors
- Caohui Duan (ORCID: https://orcid.org/0000-0002-3470-5602)
- M Arkin
- Xin Lou (ORCID: https://orcid.org/0000-0003-2980-5171)
- Longsheng Pan (ORCID: https://orcid.org/0000-0002-1033-1802)
- Song Wang (ORCID: https://orcid.org/0000-0001-7122-013X)
- Ming Zhang (ORCID: https://orcid.org/0000-0003-1076-1973)
- Xiangbing Bian (ORCID: https://orcid.org/0000-0002-7016-6503)
- Xin Hua Zhou (ORCID: https://orcid.org/0000-0002-5580-7907)
- Yongqin Xiong (ORCID: https://orcid.org/0000-0002-2435-9064)
- Haoxuan Lu
- Li Yan (ORCID: https://orcid.org/0000-0001-5427-2552)
- Xuemei Li (ORCID: https://orcid.org/0000-0003-1194-8481)
- Mingliang Yang (ORCID: https://orcid.org/0000-0002-6026-4740)
- Lu‐Hua Zhang (ORCID: https://orcid.org/0000-0003-0298-9388)
- Xiaojing Ren
Institutions
- Beijing Institute of Technology (CN)
- Peking University (CN)
- Chinese PLA General Hospital (CN)
- Beijing University of Technology (CN)
- Wuhan Institute of Physics and Mathematics (CN)
- Peking University International Hospital (CN)
- Beijing International Studies University (CN)
Publication Details
- Journal
- Journal of neurosurgery
- Published
- 2025-09-12
- DOI
- https://doi.org/10.3171/2025.5.jns25291
- Primary Topic
- Ultrasound and Hyperthermia Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00