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Scale invariant texture descriptors for classifying celiac disease / Sebastian Hegenbart, Andreas Uhl, Andreas Vécsei, Georg Wimmer
AuthorHegenbart, Sebastian ; Uhl, Andreas ; Vécsei, Andreas ; Wimmer, Georg
Published in
Medical Image Analysis, Amsterdam, 2013, Vol. 2013, Issue 17, page 458-474
PublishedElsevier Science, 2013
Document typeJournal Article
Keywords (EN)scale_invariance / texture_recognition / celiac_disease
URNurn:nbn:at:at-ubs:3-510 Persistent Identifier (URN)
 The work is publicly available
Scale invariant texture descriptors for classifying celiac disease [1.99 mb]
Abstract (English)

Scale invariant texture recognition methods are applied for the computer assisted diagnosis of celiac disease.In particular, emphasis is given to techniques enhancing the scale invariance of multi-scale and multi-orientation wavelet transforms and methods based on fractal analysis. After fine-tuning to specific properties of our celiac disease imagery database, which consists of endoscopic images of the duodenum, some scale invariant (and often even viewpoint invariant) methods provide classification results improving the current state of the art. However, not each of the investigated scale invariant methods is applicable successfully to our dataset. Therefore, the scale invariance of the employed approaches is explicitly assessed and it is found that many of the analyzed methods are not as scale invariant as they theoretically should be. Results imply that scale invariance is not a key-feature required for successful classification of our celiac disease dataset