First steps into endoscopic video analysis for Barrett's cancer detection: Challenges and opportunities

Joost van der Putten, Jeroen de Groof, Fons van der Sommen, Maarten Struyvenberg, Svitlana Zinger, Wouter Curvers, Erik Schoon, Jacques Bergman, Peter H.N. de With

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

1 Citation (Scopus)

Abstract

Routine surveillance endoscopies are currently used to detect dysplasia in patient with Barrett's Esophagus (BE). However, most of these procedures are performed by non-expert endoscopists in community hospitals. Leading to many missed dysplastic lesions, which can progress into advanced esophageal adenocarcinoma if left untreated.1 In recent years, several successful algorithms have been proposed for the detection of cancer in BE using high-quality overview images. This work addresses the first steps towards clinical application on endoscopic surveillance videos. Several challenges are identified that occur when moving from image-based to video-based analysis. (1) It is shown that algorithms trained on high-quality overview images do not naively transfer to endoscopic videos due to e.g. non-informative frames. (2) Video quality is shown to be an important factor in algorithm performance. Specifically, temporal location performance is highly correlated with video quality. (3) When moving to real-time algorithms, the additional compute necessary to address the challenges in videos will become a burden on the computational budget. However, in addition to challenges, videos also bring new opportunities not available in the current image-based methods such as the inclusion of temporal information. This work shows that a multi-frame approach increases performance compared to a naive single-image method when the above challenges are addressed.

Original languageEnglish
Title of host publicationMedical Imaging 2020
Subtitle of host publicationComputer-Aided Diagnosis
EditorsHorst K. Hahn, Maciej A. Mazurowski
PublisherSPIE
Number of pages7
ISBN (Electronic) 9781510633964
ISBN (Print)9781510633957
DOIs
Publication statusPublished - 2020
EventSPIE Medical Imaging 2020 - Houston, United States
Duration: 15 Feb 202020 Feb 2020

Publication series

NameProceedings of SPIE
Volume11314
ISSN (Print)1605-7422

Conference

ConferenceSPIE Medical Imaging 2020
Country/TerritoryUnited States
CityHouston
Period15/02/2020/02/20

Keywords

  • barrett's esophagus
  • multi-frame classication
  • real-time
  • temporal localization

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