Albisser, Zeno, Riegler, Michael, Halvorsen, Pål, Zhou, Jiang ORCID: 0000-0002-3067-8512, Griwodz, Carsten, Balasingham, IIangko and Gurrin, Cathal ORCID: 0000-0003-2903-3968 (2015) Expert driven semi-supervised elucidation tool for medical endoscopic videos. In: MMSys 2015, 18-20 March 2015, Portland, Oregon. ISBN 978-1-4503-3351-1
Abstract
In this paper, we present a novel application for elucidating all kind of videos that require expert knowledge, e.g., sport videos, medical videos etc., focusing on endoscopic surgery and video capsule endoscopy. In the medical domain, the knowledge of experts for tagging and interpretation of videos is of high value. As a result of the stressful working environment of medical doctors, they often simply do not have time for extensive annotations. We therefore present a semi-supervised method to gather the annotations in a very easy and time saving way for the experts and we show how this information can be used later on.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Endoscopic video; Polyp; Semi-supervised |
Subjects: | Computer Science > Image processing Computer Science > Information retrieval |
DCU Faculties and Centres: | Research Institutes and Centres > INSIGHT Centre for Data Analytics DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing |
Published in: | MMSys '15 Proceedings of the 6th ACM Multimedia Systems Conference. . Association for Computing Machinery. ISBN 978-1-4503-3351-1 |
Publisher: | Association for Computing Machinery |
Official URL: | http://dx.doi.org/10.1145/2713168.2713184 |
Copyright Information: | © ACM, 2015. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MMSys '15 Proceedings of the 6th ACM Multimedia Systems Conference http://doi.acm.org/10.1145/2713168.2713184 |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 20509 |
Deposited On: | 25 Mar 2015 11:52 by Jiang Zhou . Last Modified 25 Jan 2019 10:14 |
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