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Proceedings Paper

Object classification in images for Epo doping control based on fuzzy decision trees
Author(s): Ivan Bajla; Igor Hollander; Dorothea Heiss; Reinhard Granec; Markus Minichmayr
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Paper Abstract

Erythropoietin (Epo) is a hormone which can be misused as a doping substance. Its detection involves analysis of images containing specific objects (bands), whose position and intensity are critical for doping positivity. Within a research project of the World Anti-Doping Agency (WADA) we are implementing the GASepo software that should serve for Epo testing in doping control laboratories world-wide. For identification of the bands we have developed a segmentation procedure based on a sequence of filters and edge detectors. Whereas all true bands are properly segmented, the procedure generates a relatively high number of false positives (artefacts). To separate these artefacts we suggested a post-segmentation supervised classification using real-valued geometrical measures of objects. The method is based on the ID3 (Ross Quinlan's) rule generation method, where fuzzy representation is used for linking the linguistic terms to quantitative data. The fuzzy modification of the ID3 method provides a framework that generates fuzzy decision trees, as well as fuzzy sets for input data. Using the MLTTM software (Machine Learning Framework) we have generated a set of fuzzy rules explicitly describing bands and artefacts. The method eliminated most of the artefacts. The contribution includes a comparison of the obtained misclassification errors to the errors produced by some other statistical classification methods.

Paper Details

Date Published: 23 February 2005
PDF: 15 pages
Proc. SPIE 5673, Applications of Neural Networks and Machine Learning in Image Processing IX, (23 February 2005); doi: 10.1117/12.585255
Show Author Affiliations
Ivan Bajla, ARC Seibersdorf Research GmbH (Austria)
Igor Hollander, ARC Seibersdorf Research GmbH (Austria)
Dorothea Heiss, ARC Seibersdorf Research GmbH (Austria)
Reinhard Granec, ARC Seibersdorf Research GmbH (Austria)
Markus Minichmayr, ARC Seibersdorf Research GmbH (Austria)


Published in SPIE Proceedings Vol. 5673:
Applications of Neural Networks and Machine Learning in Image Processing IX
Nasser M. Nasrabadi; Syed A. Rizvi, Editor(s)

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