Robust spectral analysis of videocapsule images acquired from celiac disease patients

Dominant 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.

The 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.

For 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.

The 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.