@Article{GloriaFernandezEsparrach2016,
author="Gloria Fernandez Esparrach
and Jorge Bernal
and Maria Lopez Ceron
and Henry Cordova
and Cristina Sanchez Montes
and Cristina Rodriguez de Miguel
and F. Javier Sanchez",
title="Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps",
journal="Endoscopy",
year="2016",
volume="48",
number="9",
pages="837--842",
abstract="Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly in 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 which represent the likelihood of polyp presence.Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. Mean values of the maximum of energy map were higher in 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). Using 3.75 as maximum threshold value, sensitivity and specificity for 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 showed a good performance for colonic polyp detection. This indicates a potential applicability in clinical practice.",
optnote="MV;",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2778), last updated on Thu, 16 Feb 2023 11:57:45 +0100",
doi="10.1055/s-0042-108434",
file=":http://refbase.cvc.uab.es/files/FBL2016.pdf:PDF"
}