ArticleBiomedical engineering online2011
Robust spectral analysis of videocapsule images acquired from celiac disease patients.
Article in Biomedical engineering online, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Automated diagnosis of celiac disease by video capsule endoscopy using DAISY Descriptors.Journal of medical systems · 2019Article
- Coeliac disease and the videocapsule: what have we learned till now.Annals of translational medicine · 2017Review
- Overview of technical solutions and assessment of clinical usefulness of capsule endoscopy.Biomedical engineering online · 2015Review
- Quantitative image analysis of celiac disease.World journal of gastroenterology · 2015Review
- Implementation of a polling protocol for predicting celiac disease in videocapsule analysis.World journal of gastrointestinal endoscopy · 2013Article
- Quantitative estimates of motility from videocapsule endoscopy are useful to discern celiac patients from controls.Digestive diseases and sciences · 2012Article
- Improved frequency resolution for characterization of complex fractionated atrial electrograms.Biomedical engineering online · 2012Article
- Identification of recurring patterns in fractionated atrial electrograms using new transform coefficients.Biomedical engineering online · 2012Article
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5 authors.
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Abstract
backgroundDominant frequency (DF) analysis of videocapsule endoscopy images is a new method to detect small intestinal periodicities that may result from mechanical rhythms such as peristalsis. Longer periodicity is related to greater image texture at areas of villous atrophy in celiac disease. However, extraneous features and spatiotemporal phase shift may mask DF rhythms.
methodThe robustness of Fourier and ensemble averaging spectral analysis to compute DF was tested. Videocapsule images from the distal duodenum of 11 celiac patients (frame rate 2/s and pixel resolution 576 × 576) were analyzed. For patients 1, 2, ... 11, respectively, a total of 10, 11, ..., 20 sequential images were extracted from a randomly selected time epoch. Each image sequence was artificially repeated to 200 frames, simulating periodicities of 0.2, 0.18, ..., 0.1Hz, respectively. Random white noise at four different levels, spatiotemporal phase shift, and frames with air bubbles were added. Power spectra were constructed pixel-wise over 200 frames, and an average spectrum was computed from the 576 × 576 individual spectra. The largest spectral peak in the average spectrum was the estimated DF. Error was defined as the absolute difference between actual DF and estimated DF.
resultsFor Fourier analysis, the mean absolute error between estimated and actual DF was 0.032 ± 0.052Hz. Error increased with greater degree of random noise imposed. In contrast, all ensemble average estimates precisely predicted the simulated DF.
conclusionsThe ensemble average DF estimate of videocapsule images with simulated periodicity is robust to noise and spatiotemporal phase shift as compared with Fourier analysis. Accurate estimation of DF eliminates the need to impose complex masking, extraction, and/or corrective preprocessing measures.
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