Evaluation of Different Distortion Correction Methods and Interpolation Techniques for an Automated Classification of Celiac Disease

Due to the optics used in endoscopes, a typical degradation observed in endoscopic images are barrel-type distortions. In this work we investigate the impact of methods used to correct such distortions in images on the classification accuracy in the context of automated celiac disease classification. For this purpose we compare various different distortion correction methods and apply them to endoscopic images, which are subsequently classified. Since the interpolation used in such methods is also assumed to have an influence on the resulting classification accuracies, we also investigate different interpolation methods and their impact on the classification performance. In order to be able to make solid statements about the benefit of distortion correction we use various different feature extraction methods used to obtain features for the classification. Our experiments show that it is not possible to make a clear statement about the usefulness of distortion correction methods in the context of an automated diagnosis of celiac disease. This is mainly due to the fact that an eventual benefit of distortion correction highly depends on the feature extraction method used for the classification

Capturing correlation changes by applying kernel change point detection on the running correlations

© 2018 Elsevier Inc. Change point detection methods signal the occurrence of abrupt changes in a time series. Non-parametric approaches, such as the Gaussian kernel based change point (KCP) detection (Arlot et al., 2012), are especially attractive because they impose less assumptions on the data. Yet, a drawback of these methods is that most of them are sensitive to changes in the mean, the variance, etc., making them less sensitive to specific kinds of changes. We show that KCP can be adapted to detect a particular type of change only. We focus here on correlation change, which has been put forward by different theories but proved hard to trace in multivariate time series. We propose KCP-corr, which boils down to applying KCP on the running correlations. To confirm that KCP-corr is more sensitive than merely applying KCP on the raw data (KCP-raw), a simulation study was conducted in which the number of (noise) variables and the size of the correlation change were varied. KCP-corr emerged as the better method especially in the more difficult but realistic settings where the correlation change is minimal and/or noise variables are present. KCP-corr also outperforms Cusum, a non-parametric method that specifically targets the detection of correlation changes.status: publishe

No haste, more taste: An EMA study of the effects of stress, negative and positive emotions on eating behavior

OBJECTIVES: Stress and emotions alter eating behavior in several ways: While experiencing negative or positive emotions typically leads to increased food intake, stress may result in either over- or undereating. Several participant characteristics, like gender, BMI and restrained, emotional, or external eating styles seem to influence these relationships. Thus far, most research relied on experimental laboratory studies, thereby reducing the complexity of real-life eating episodes. The aim of the present study was to delineate the effects of stress, negative and positive emotions on two key facets of eating behavior, namely taste- and hunger-based eating, in daily life using ecological momentary assessment (EMA). Furthermore, the already mentioned individual differences as well as time pressure during eating, an important but unstudied construct in EMA studies, were examined. METHODS: Fifty-nine participants completed 10days of signal-contingent sampling and data were analyzed using multilevel modeling. RESULTS: Results revealed that higher stress led to decreased taste-eating which is in line with physiological stress-models. Time pressure during eating resulted in less taste- and more hunger-eating. In line with previous research, stronger positive emotions went along with increased taste-eating. Emotional eating style moderated the relationship between negative emotions and taste-eating as well as hunger-eating. BMI moderated the relationship between negative as well as positive emotions and hunger-eating. CONCLUSIONS: These findings emphasize the importance of individual differences for understanding eating behavior in daily life. Experienced time pressure may be an important aspect for future EMA eating studies.status: publishe