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Titel
Scale invariant texture descriptors for classifying celiac disease / Sebastian Hegenbart, Andreas Uhl, Andreas Vécsei, Georg Wimmer
VerfasserHegenbart, Sebastian ; Uhl, Andreas ; Vécsei, Andreas ; Wimmer, Georg
Erschienen in
Medical Image Analysis, Amsterdam, 2013, Jg. 2013, H. 17, S. 458-474
ErschienenElsevier Science, 2013
UmfangIllustrationen
SpracheEnglisch
DokumenttypAufsatz in einer Zeitschrift
Schlagwörter (EN)scale_invariance / texture_recognition / celiac_disease
ISSN1361-8415
URNurn:nbn:at:at-ubs:3-510 Persistent Identifier (URN)
DOI10.1016/j.media.2013.02.001 
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 Das Werk ist frei verfügbar
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Scale invariant texture descriptors for classifying celiac disease [1.99 mb]
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Zusammenfassung (Englisch)

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