Complex wavelet transform variants in a scale invariant classification of celiac disease

Authors:
Andreas Uhl;Andreas Vécsei;Georg Wimmer
Affiliations:
Department of Computer Sciences, University of Salzburg, Salzburg, Austria;St. Anna Children's Hospital, Vienna, Austria;Department of Computer Sciences, University of Salzburg, Salzburg, Austria
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

Citing 3
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Abstract

In this paper, we present variants of the Dual-Tree Complex Wavelet Transform (DT-CWT) in order to automatically classify endoscopic images with respect to the Marsh classification. The feature vectors either consist of the means and standard deviations of the subbands from a DT-CWT variant or of the Weibull parameter of these subbands. To reduce the effects of different distances and perspectives toward the mucosa, we enhanced the scale invariance by applying the discrete Fourier transform or the discrete cosine transform across the scale dimension of the feature vector.