Conference Proceeding
Towards automated diagnosis of celiac disease by computer-assisted classification of duodenal imagery
St. Anna Children's Hosp., Vienna
08/2008;
ISBN: 978-0-86341-934-8 pp.1 - 4 In proceeding of: Advances in Medical, Signal and Information Processing, 2008. MEDSIP 2008. 4th IET International Conference on
Source: IEEE Xplore
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Citations (0)
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Article: Experimental study on the impact of endoscope distortion correction on computer-assisted celiac disease diagnosis
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ABSTRACT: information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Abstract— The impact of applying barrel distortion cor-rection to endoscopic imagery in the context of automated celiac disease diagnosis is experimentally investigated. For a large set of feature extraction techniques, it is found that contrasting to intuition, no improvement but even significant result degradation of classification accuracy can be observed. For techniques relying on geometrical properties of the image material ("shape"), moderate improvements of classification accuracy can be achieved. Reasons for this somewhat unex-pected results are discussed and ways how to exploit potential distortion correction benefits are sketched.
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Keywords
automated classification
Bayes classifier
detection
duodenal imagery
mucosal damage typical
Spatial domain
specificity
subsequent classification
techniques
texture classification
various algorithms
Various techniques
