Automated measurement of quality of mucosa inspection for colonoscopy

Xuemin Liu, Wallapak Tavanapong, Johnny Wong, Jung Hwan Oh, Piet C. De Groen

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Colonoscopy is currently the preferred screening modality for prevention of colorectal cancer. However, the effectiveness of colonoscopy depends on the quality of the procedure, which depends on several factors. In this paper, we present new methods that derive a new quality metric for automated scoring of quality of mucosa inspection performed by the endoscopist. We conducted Pearson's Correlation analysis of the computerized metric scores against the averages of the manual scores given by four domain experts on twenty-one colonoscopy videos. Our metric shows a relatively strong positive correlation (Pearson's correlation coefficient of 0.72) between the computer-generated score and the ground truth. Hence, the proposed work is very promising to be used for quality control/assurance in routine colonoscopy screening.

Original languageEnglish (US)
Pages (from-to)951-960
Number of pages10
JournalProcedia Computer Science
Volume1
Issue number1
DOIs
StatePublished - Jan 1 2010

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Keywords

  • Image analysis
  • Objective quality metrics
  • Quality of colonoscopy

ASJC Scopus subject areas

  • Computer Science(all)

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