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Semi-automated Query Construction for Content-Based Endomicroscopy Video Retrieval

  • Marzieh Kohandani Tafresh
  • Nicolas Linard
  • Barbara André
  • Nicholas Ayache
  • Tom Vercauteren
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

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.

Keywords

Scale Invariant Feature Transform Video Retrieval Confocal Laser Endomicroscopy Temporal Segmentation Scale Invariant Feature Transform Descriptor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Marzieh Kohandani Tafresh
    • 1
    • 2
  • Nicolas Linard
    • 2
  • Barbara André
    • 2
  • Nicholas Ayache
    • 1
  • Tom Vercauteren
    • 2
  1. 1.Inria Asclepios Project-TeamSophia AntipolisFrance
  2. 2.Mauna Kea TechnologiesParisFrance

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