Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps

Glòria Fernández-Esparrach, Jorge Bernal, Maria López-Cerón, Henry Córdova, Cristina Sánchez-Montes, Cristina Rodríguez De Miguel, Francisco Javier Sánchez

Research output: Contribution to journalArticleResearchpeer-review

108 Citations (Scopus)

Abstract

© Georg Thieme Verlag KG Stuttgart New York. Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly for small polyps. We explored the efficacy of an automatic computer-vision method for polyp detection. Methods: Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps that represent the likelihood of the presence of a polyp. Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. The mean of the maximum values on the energy map was higher for frames with polyps than without (P<0.001). Performance improved in high quality frames (AUC=0.79 [95%CI 0.70-0.87] vs. 0.75 [95%CI 0.66-0.83]). With 3.75 set as the maximum threshold value, sensitivity and specificity for the detection of polyps were 70.4% (95%CI 60.3%-80.8%) and 72.4% (95%CI 61.6%-84.6%), respectively. Conclusion: Energy maps performed well for colonic polyp detection, indicating their potential applicability in clinical practice.
Original languageEnglish
Pages (from-to)837-842
JournalEndoscopy
Volume48
DOIs
Publication statusPublished - 1 Sept 2016

Fingerprint

Dive into the research topics of 'Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps'. Together they form a unique fingerprint.

Cite this