Zisimopoulos, O;
Flouty, E;
Luengo, I;
Giataganas, P;
Nehme, J;
Chow, A;
Stoyanov, D;
(2018)
DeepPhase: Surgical Phase Recognition in CATARACTS Videos.
In: Frangi, A and Schnabel, J and Davatzikos, C and Alberola-López, C and Fichtinger, G, (eds.)
Medical Image Computing and Computer Assisted Intervention (MICCAI 2018): 21st International Conference, Proceedings, Part IV.
(pp. pp. 265-272).
Springer: Cham, Switzerland.
Preview |
Text
DeepPhase.pdf - Accepted Version Download (7MB) | Preview |
Abstract
Automated surgical workflow analysis and understanding can assist surgeons to standardize procedures and enhance post-surgical assessment and indexing, as well as, interventional monitoring. Computer-assisted interventional (CAI) systems based on video can perform workflow estimation through surgical instruments’ recognition while linking them to an ontology of procedural phases. In this work, we adopt a deep learning paradigm to detect surgical instruments in cataract surgery videos which in turn feed a surgical phase inference recurrent network that encodes temporal aspects of phase steps within the phase classification. Our models present comparable to state-of-the-art results for surgical tool detection and phase recognition with accuracies of 99 and 78% respectively.
| Type: | Proceedings paper |
|---|---|
| Title: | DeepPhase: Surgical Phase Recognition in CATARACTS Videos |
| Event: | MICCAI 2018, 21st International Conference, 16-20 September 2018, Granada, Spain |
| ISBN-13: | 978-3-030-00936-6 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-00937-3_31 |
| Publisher version: | https://doi.org/10.1007/978-3-030-00937-3_31 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Surgical vision, instrument detection, surgical workflow, deep learning, surgical data science |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10060022 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
