Texture-based classification of confocal laser endomicroscopy images for Barrett’s esophagus surveillanceDownload PDF

07 Jul 2019 (modified: 05 May 2023)Submitted to COMPAY 2019Readers: Everyone
Keywords: Barrett’s esophagus, confocal laser endomicroscopy, texture analysis, fractal local density, image classification
Abstract: Barrett’s esophagus is a complication of gastroesophageal reflux diseases that generates a transformation of esophagus epithelium turning into adenocarcinoma with a high risk. The surveillance of the changes in the esophageal mucosa is primordial to estimate the cancer progression. Confocal laser endomicroscopy is a novel imaging technique allowing physicians to perform in-vivo and real-time histological analysis in order to decrease the number of biopsies needed for the diagnosis. This paper uses the notion of local density function to extract characteristic morphologies of tissues. This allows us to define a novel classification method for Barrett’s images based on fractal textures. The method performs particularly well on pre-cancer stages with an overall accuracy of 89.2%.
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