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MOSaiC: a Web-based Platform for Collaborative Medical Video Assessment and Annotation

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arxiv 2312.08593 v1 pith:H4PZUNEF submitted 2023-12-14 cs.CV

Jean-Paul Mazellier , Antoine Boujon , Méline Bour-Lang , Maël Erharhd , Julien Waechter , Emilie Wernert , Pietro Mascagni , Nicolas Padoy This is my paper · ORCID
classification cs.CV
keywords mosaicannotationassessmentmedicalcollaborativedataplatformscience
verification ladder T0 review T1 audit T2 compute T3 formal
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This technical report presents MOSaiC 3.6.2, a web-based collaborative platform designed for the annotation and evaluation of medical videos. MOSaiC is engineered to facilitate video-based assessment and accelerate surgical data science projects. We provide an overview of MOSaiC's key functionalities, encompassing group and video management, annotation tools, ontologies, assessment capabilities, and user administration. Finally, we briefly describe several medical data science studies where MOSaiC has been instrumental in the dataset development.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 4 citations worldwide. Full citation record

  1. SPIRIT: Spatio-temporal Pairwise Relational Modeling of Instrument-Tissue Interactions for Surgical Action Triplet Recognition

    cs.CV 2026-08 conditional novelty 6.0 of 10

    Explicit pairwise relational modeling improves multi-center surgical action triplet recognition, demonstrated on a new four-center Roux-en-Y gastric bypass dataset.

  2. When do they StOP?: A First Step Towards Automatically Identifying Team Communication in the Operating Room

    cs.CV 2025-02 conditional novelty 6.0 of 10

    A new Team-OR dataset with 55 annotated team briefings in 105 hours of real OR video, plus a detection model that outperforms baseline temporal action detectors.

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