Endoscope distortion correction does not (easily) improve mucosa-based classification of celiac disease

Jutta Hämmerle-Uhl, Yvonne Höller, Andreas Uhl, Andreas Vécsei

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Distortion correction is applied to endoscopic duodenal imagery to improve automated classification of celiac disease affected mucosa patches. In a set of six edge- and shape-related feature extraction techniques, only a single one is able to consistently benefit from distortion correction, while for others, even a decrease of classification accuracy is observed. Different types of distortion correction do not lead to significantly different behaviour in the observed application scenario.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
EditorsNicholas Ayache, Herve Delingette, Polina Golland, Kensaku Mori
PublisherSpringer Verlag
Pages574-581
Number of pages8
ISBN (Print)9783642334535
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 - Nice, France
Duration: 1 Oct 20125 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7512 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
Country/TerritoryFrance
CityNice
Period1/10/125/10/12

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2012.

Other keywords

  • Automated classification
  • Celiac disease
  • Endoscope distortion correction
  • Shape- and edge-based features

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