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Expert driven semi-supervised elucidation tool for medical endoscopic videos
Albisser, Zeno; Riegler, Michael; Halvorsen, Pål; Zhou, Jiang; Griwodz, Carsten; Balasingham, IIangko; Gurrin, Cathal
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.
Keyword(s): Image processing; Information retrieval
Publication Date:
2015
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Publisher(s): Association for Computing Machinery
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/20509/,
http://dx.doi.org/10.1145/2713168.2713184
First Indexed: 2015-03-26 05:19:26 Last Updated: 2018-10-13 06:12:05