Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps
Fernández-Esparrach, Gloria (Hospital Clínic i Provincial de Barcelona)
Bernal del Nozal, Jorge (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)
Lopez-Ceron, Maria (Hospital Clínic i Provincial de Barcelona)
Córdova, Henry (Hospital Clínic i Provincial de Barcelona)
Sánchez-Montes, Cristina (Hospital Clínic i Provincial de Barcelona)
Rodríguez De Miguel, Cristina (Hospital Clínic i Provincial de Barcelona)
Sánchez, F. Javier (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)

Date:	2016
Abstract:	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.
Grants:	Ministerio de Economía y Competitividad DPI2015-65286-R Generalitat de Catalunya 2014/SGR-135 Generalitat de Catalunya 2014/SGR-1470
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Language:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Published in:	Endoscopy, Vol. 48, Num. 9 (2016) , p. 837-842, ISSN 1438-8812

DOI: 10.1055/s-0042-108434

Postprint 20 p, 754.6 KB

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