Semi-automated Query Construction for Content-based Endomicroscopy Video Retrieval - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

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

Nicolas Linard
  • Function : Author
  • PersonId : 938075
Barbara André
  • Function : Author
  • PersonId : 902248
Tom Vercauteren
  • Function : Author
  • PersonId : 856920


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.
Fichier principal
Vignette du fichier
paper-841.pdf (293.37 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01010673 , version 1 (20-06-2014)


  • HAL Id : hal-01010673 , version 1


Marzieh Kohandani Tafreshi, Nicolas Linard, Barbara André, Nicholas Ayache, Tom Vercauteren. Semi-automated Query Construction for Content-based Endomicroscopy Video Retrieval. Medical Image Computing and Computer Assisted Intervention (MICCAI), Sep 2014, Boston, United States. ⟨hal-01010673⟩


170 View
247 Download


Gmail Facebook Twitter LinkedIn More