An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis.

Barbara André, Tom Vercauteren, Anna M. Buchner, Muhammad Waseem Shahid, Michael B Wallace, Nicholas Ayache

Research output: Chapter in Book/Report/Conference proceedingChapter

14 Citations (Scopus)

Abstract

Learning medical image interpretation is an evolutive process that requires modular training systems, from non-expert to expert users. Our study aims at developing such a system for endomicroscopy diagnosis. It uses a difficulty predictor to try and shorten the physician learning curve. As the understanding of video diagnosis is driven by visual similarities, we propose a content-based video retrieval approach to estimate the level of interpretation difficulty. The performance of our retrieval method is compared with several state of the art methods, and its genericity is demonstrated with two different clinical databases, on the Barrett's Esophagus and on colonic polyps. From our retrieval results, we learn a difficulty predictor against a ground truth given by the percentage of false diagnoses among several physicians. Our experiments show that, although our datasets are not large enough to test for statistical significance, there is a noticeable relationship between our retrieval-based difficulty estimation and the difficulty experienced by the physicians.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages480-487
Number of pages8
Volume13
EditionPt 2
StatePublished - 2010

Fingerprint

Physicians
Colonic Polyps
Expert Systems
Learning Curve
Barrett Esophagus
Learning
Databases
Datasets

ASJC Scopus subject areas

  • Medicine(all)

Cite this

André, B., Vercauteren, T., Buchner, A. M., Shahid, M. W., Wallace, M. B., & Ayache, N. (2010). An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 2 ed., Vol. 13, pp. 480-487)

An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis. / André, Barbara; Vercauteren, Tom; Buchner, Anna M.; Shahid, Muhammad Waseem; Wallace, Michael B; Ayache, Nicholas.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 13 Pt 2. ed. 2010. p. 480-487.

Research output: Chapter in Book/Report/Conference proceedingChapter

André, B, Vercauteren, T, Buchner, AM, Shahid, MW, Wallace, MB & Ayache, N 2010, An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 2 edn, vol. 13, pp. 480-487.
André B, Vercauteren T, Buchner AM, Shahid MW, Wallace MB, Ayache N. An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 2 ed. Vol. 13. 2010. p. 480-487
André, Barbara ; Vercauteren, Tom ; Buchner, Anna M. ; Shahid, Muhammad Waseem ; Wallace, Michael B ; Ayache, Nicholas. / An image retrieval approach to setup difficulty levels in training systems for endomicroscopy diagnosis. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 13 Pt 2. ed. 2010. pp. 480-487
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