Reinforcement learning for safe autonomous two-device navigation of cerebral vessels in mechanical thrombectomy
To the best of our knowledge, our proposed autonomous system for MT two-device navigation reaches cerebral vessels, considers safety, and is generalizable to unseen patient-specific cases for the first time. We envisage future work will extend the validation to vasculatures of different complexity and on in vitro models. While our contributions pave the way toward deploying agents in clinical settings, safety and trustworthiness will be crucial elements to consider when proposing new methodology.
Authors
- Thomas C. Booth (ORCID: https://orcid.org/0000-0003-0984-3998)
- Benjamin M. Jackson
- Lennart Karstensen
- Harry Robertshaw (ORCID: https://orcid.org/0000-0002-5486-8062)
- Jiaheng Wang (ORCID: https://orcid.org/0000-0002-9783-5471)
- Alejandro Granados (ORCID: https://orcid.org/0000-0002-2866-1324)
- Hadi Sadati
Institutions
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- King's College London (GB)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1007/s11548-025-03339-8
- Citations
- 6
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 8.13
Funders
- Wellcome Trust
- University of Oxford
- Engineering and Physical Sciences Research Council