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Background: Videocapsule endoscopy images are useful to detect pathologic alterations, including villous atrophy, in the small intestinal mucosa, which is helpful for diagnosing celiac disease. In prior work, quantitative videocapsule analysis was found useful to classify celiac versus control images. However, the effect of dark/extraneous substances on classification efficacy requires remediation., Method: For quantitative analysis, data from the Medtronic SB2 and SB3 systems were pooled. Videocapsule images of the distal duodenum/proximal jejunum were acquired from 13 celiac and 13 control patients. Dark regions, extraneous fluids, and air bubbles were mostly removed by utilizing color masking. Two different red-green-blue (RGB) color masks were constructed from 20 to 30 reference pixels obtained from mucosal and from extraneous regions. Each image pixel was accepted or rejected for subsequent analysis based on whether its distance was closest to a mucosal or to an extraneous reference in RGB space. Four images were then randomly selected from each videoclip for processing (52 images from each group). After masking, celiac versus control images were plotted in a three-space consisting of mean and standard deviation in pixel brightness, and surface area remaining after masking. A linear discriminant function was used for classification. The paradigm was repeated with a second random data set for validation., Results: Masking improved classification of celiac versus control images to nearly 80% accuracy as compared to 70-77% without masking. Celiac disease patients tended to have lesser mean pixel brightness and greater variability in brightness, in accord with prior work, and more masking was needed to remove extraneous features., Conclusions: Color masking is useful to remove dim/extraneous features from videocapsule images and it results in improved classification/assessment to distinguish celiac with villous atrophy from control videocapsule image. This can be helpful to detect and map regions of pathology, to screen for celiac disease, and to determine the efficacy of a gluten free diet., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Videocapsule endoscopy is a relative new method to analyze the gastrointestinal tract for the presence of pathologic features. It is of relevance to detect villous atrophy in the small bowel, which is a defining symptom of celiac disease., Method: In this tutorial, methods to extract and process videocapsule endoscopy data are elucidated. The algorithms, computer code, and paradigms to analyze image series are described in detail. The topics covered include extraction of data, analysis of texture, eigenanalysis, spectral analysis, three-dimensional projection, and estimation of motility. The basic paradigms to implement these processes are provided., Results: Examples of successful quantitative analysis implementations for selected untreated celiac disease patients with villous atrophy versus control patients with normal villi were illustrated. Based on the implementations, it was evident that celiac patients tended to have a rougher small intestinal texture as compared with control patients. From three-dimensional projection, celiac patients exhibited larger surface protrusions emanating from the small intestinal mucosa, which may represent clumps of atrophied villi. The periodicity of small intestinal contractions tends to be slower when villous atrophy is present, and the estimated degree of motility is reduced as compared with control image series. Basis image construction suggested that fissuring and mottling of the mucosal surface is predominant in untreated celiac patients, and mostly absent in controls., Conclusions: Implementation of computerized methods, as described in this tutorial, will likely be useful for the automated detection and measurement of villous atrophy, and to map its extent along the small intestine of celiac patients., (Copyright © 2016 Elsevier Ltd. All rights reserved.)