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Semi-automated query construction for content-based endomicroscopy video retrieval

Tafreshi, MK; Linard, N; André, B; Ayache, N; Vercauteren, T; (2014) Semi-automated query construction for content-based endomicroscopy video retrieval. In: Proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention: MICCAI 2014. (pp. pp. 89-96). Springer, Cham: Boston, MA, USA. Green open access

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Abstract

Content-based video retrieval has shown promising results to help physicians in their interpretation of medical videos in general and endomicroscopic ones in particular. Defining a relevant query for CBVR can however be a complex and time-consuming task for non-expert and even expert users. Indeed, uncut endomicroscopy videos may very well contain images corresponding to a variety of different tissue types. Using such uncut videos as queries may lead to drastic performance degradations for the system. In this study, we propose a semi-automated methodology that allows the physician to create meaningful and relevant queries in a simple and efficient manner. We believe that this will lead to more reproducible and more consistent results. The validation of our method is divided into two approaches. The first one is an indirect validation based on per video classification results with histopathological ground-truth. The second one is more direct and relies on perceived inter-video visual similarity ground-truth. We demonstrate that our proposed method significantly outperforms the approach with uncut videos and approaches the performance of a tedious manual query construction by an expert. Finally, we show that the similarity perceived between videos by experts is significantly correlated with the inter-video similarity distance computed by our retrieval system.

Type: Proceedings paper
Title: Semi-automated query construction for content-based endomicroscopy video retrieval
Event: 17th International Conference on Medical Image Computing and Computer-Assisted Intervention: MICCAI 2014
Location: Germany
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-10404-1_12
Publisher version: https://doi.org/10.1007/978-3-319-10404-1_12
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Algorithms, Colonic Polyps, Colonoscopy, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Information Storage and Retrieval, Microscopy, Reproducibility of Results, Sensitivity and Specificity, User-Computer Interface, Scale Invariant Feature Transform, Video Retrieval, Confocal Laser Endomicroscopy, Temporal Segmentation, Scale Invariant Feature Transform Descriptor
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1450866
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