ConsisTNet: a spatio-temporal approach for consistent anatomical localization in endoscopic pituitary surgery
ConsisTNet demonstrates significant improvements in spatio-temporal consistency of anatomical localization during endoscopic pituitary surgery, providing more stable and reliable real-time surgical assistance.
Authors
- Danyal Z. Khan (ORCID: https://orcid.org/0000-0001-9213-2550)
- Simon C. Williams (ORCID: https://orcid.org/0000-0003-1770-1797)
- Zhehua Mao (ORCID: https://orcid.org/0000-0001-9225-6318)
- Adrito Das (ORCID: https://orcid.org/0000-0001-5682-9545)
- Sophia Bano (ORCID: https://orcid.org/0000-0003-1329-4565)
- Hani Joseph Marcus (ORCID: https://orcid.org/0000-0001-8000-392X)
- Danail Stoyanov (ORCID: https://orcid.org/0000-0002-0980-3227)
- John Hanrahan (ORCID: https://orcid.org/0000-0003-4584-2298)
Institutions
- The London College (GB)
- National Hospital for Neurology and Neurosurgery (GB)
- University College London (GB)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2025-04-29
- DOI
- https://doi.org/10.1007/s11548-025-03369-2
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute for Health and Care Research
- Royal Academy of Engineering
- University College London
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences
- Engineering and Physical Sciences Research Council