Estimating Withdrawal Time in Colonoscopies

Liran Katzir, Danny Veikherman, Valentin Dashinsky, Roman Goldenberg, Ilan Shimshoni, Nadav Rabani, Regev Cohen, Ori Kelner, Ehud Rivlin, Daniel Freedman

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


The Colonoscopic Withdrawal Time (CWT) is the time required to withdraw the endoscope during a colonoscopy procedure. Estimating the CWT has several applications, including as a performance metric for gastroenterologists, and as an augmentation to polyp detection systems. We present a method for estimating the CWT directly from colonoscopy video based on three separate modules: egomotion computation; depth estimation; and anatomical landmark classification. Features are computed based on the modules’ outputs, which are then used to classify each frame as representing forward, stagnant, or backward motion. This allows for the optimal detection of the change points between these phases based on efficient maximization of the likelihood; from which the CWT follows directly. We collect a dataset consisting of 788 videos of colonoscopy procedures, with the CWT for each annotated by gastroenterologists. Our algorithm achieves a mean error of 1.20 min, which nearly matches the inter-rater disagreement of 1.17 min.

Original languageEnglish
Title of host publicationComputer Vision – ECCV 2022 Workshops, Proceedings
EditorsLeonid Karlinsky, Tomer Michaeli, Ko Nishino
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages18
ISBN (Print)9783031250651
StatePublished - 2023
Event17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel
Duration: 23 Oct 202227 Oct 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13803 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th European Conference on Computer Vision, ECCV 2022
CityTel Aviv

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • Colonoscopy
  • Detection
  • Visual odometry
  • Withdrawal time

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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