DeepPhase: Surgical Phase Recognition in CATARACTS Videos
- Submitting institution
-
University College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 16217
- Type
- E - Conference contribution
- DOI
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10.1007/978-3-030-00937-3_31
- Title of conference / published proceedings
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- First page
- 265
- Volume
- 11073 LNCS
- Issue
- -
- ISSN
- 0302-9743
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
-
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Solves the problem of breaking down surgical video into clinically relevant chunks to understand process. In clinical trial at Moorefields hospital with hundreds of operations. Underpins the analytics product developed by Digital Surgery (DS) Ltd, London (contact: imanol.luengo@digitalsurgery.com). DS acquired by Medtrocic plc for half billion USD in 2020.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -