Catheter detection and segmentation in X-ray images via multi-task learning
Our approach achieves a good balance between accuracy and efficiency, making it well-suited for real-time surgical guidance applications.
Authors
- Kawal Rhode (ORCID: https://orcid.org/0000-0002-4707-7318)
- YingLiang Ma (ORCID: https://orcid.org/0000-0001-5770-5843)
- Christopher A. Rinaldi (ORCID: https://orcid.org/0000-0002-3930-1957)
- Sandra Howell (ORCID: https://orcid.org/0000-0002-3925-2913)
- Xi Lin (ORCID: https://orcid.org/0000-0001-6075-5614)
- Ethan Koland
Institutions
- University of East Anglia (GB)
- King's College London (GB)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1007/s11548-025-03461-7
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Engineering and Physical Sciences Research Council