Surgical video retrieval using deep neural networks

Varytimidis, Christos and Rapantzikos, Kostas and Loukas, Constantinos and Kollias, Stefanos (2016) Surgical video retrieval using deep neural networks. In: M2CAI 2016, 21 October 2016, Athens, Greece.

Full content URL: http://camma.u-strasbg.fr/m2cai2016/

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Abstract

Although the amount of raw surgical videos, namely videos
captured during surgical interventions, is growing fast, automatic retrieval
and search remains a challenge. This is mainly due to the nature
of the content, i.e. visually non-consistent tissue, diversity of internal organs,
abrupt viewpoint changes and illumination variation. We propose
a framework for retrieving surgical videos and a protocol for evaluating
the results. The method is composed of temporal shot segmentation and
representation based on deep features, and the protocol introduces novel
criteria to the field. The experimental results prove the superiority of
the proposed method and highlight the path towards a more effective
protocol for evaluating surgical videos.

Keywords:deep neural networks, surgical video, retrieval, new protocol
Subjects:G Mathematical and Computer Sciences > G760 Machine Learning
G Mathematical and Computer Sciences > G450 Multi-media Computing Science
G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
ID Code:26894
Deposited On:03 Apr 2017 14:22

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