title: Endoscope distortion correction does not (easily) improve mucosa-based classification of celiac disease.
abstract: Distortion correction is applied to endoscopic duodenal imagery to improve automated classification of celiac disease affected mucosa patches. In a set of six edge- and shape-related feature extraction techniques, only a single one is able to consistently benefit from distortion correction, while for others, even a decrease of classification accuracy is observed. Different types of distortion correction do not lead to significantly different behaviour in the observed application scenario.
authors.affiliation: Department of Computer Sciences, University of Salzburg, Austria.
authors.forename: Jutta
authors.initials: J
authors.lastname: Hämmerle-Uhl
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Höller
authors.forename: Andreas
authors.initials: A
authors.lastname: Uhl
authors.forename: Andreas
authors.initials: A
authors.lastname: Vécsei
mesh_terms: D016477:Artifacts; D002446:Celiac Disease / Q000473:pathology*; D016099:Endoscopy, Gastrointestinal / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007413:Intestinal Mucosa / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity