Assisted phase and step annotation for surgical videos

Gurvan Lecuyer; Martin Ragot; Nicolas Martin; Laurent Launay; Pierre Jannin

doi:10.1007/s11548-019-02108-8

Journal articles

Assisted phase and step annotation for surgical videos

Gurvan Lecuyer ^{1, 2} Martin Ragot ¹ Nicolas Martin ¹ Laurent Launay ¹ Pierre Jannin ²

1 IRT b-com - Institut de Recherche Technologique b-com

2 LTSI - Laboratoire Traitement du Signal et de l'Image

Abstract : Annotation of surgical videos is a time-consuming task which requires specific knowledge. In this paper, we present and evaluate a deep learning-based method that includes pre-annotation of the phases and steps in surgical videos and user assistance in the annotation process.

Keywords : Assisted annotation Deep learning Phase recognition Step recognition Surgical workflow

Document type :

Journal articles

Domain :

Life Sciences [q-bio] / Bioengineering

Complete list of metadatas

https://hal-univ-rennes1.archives-ouvertes.fr/hal-02498462
Contributor : Laurent Jonchère <>
Submitted on : Wednesday, March 4, 2020 - 2:51:53 PM
Last modification on : Thursday, March 5, 2020 - 1:23:17 AM

Assisted phase and step annotation for surgical videos

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Assisted phase and step annotation for surgical videos

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