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Proceedings Paper

Statistical pattern recognition algorithms for autofluorescence imaging
Author(s): Zbigniew Kulas; Elżbieta Bereś - Pawlik; Jarosław Wierzbicki
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Paper Abstract

In cancer diagnostics the most important problems are the early identification and estimation of the tumor growth and spread in order to determine the area to be operated. The aim of the work was to design of statistical algorithms helping doctors to objectively estimate pathologically changed areas and to assess the disease advancement. In the research, algorithms for classifying endoscopic autofluorescence images of larynx and intestine were used. The results show that the statistical pattern recognition offers new possibilities for endoscopic diagnostics and can be of a tremendous help in assessing the area of the pathological changes.

Paper Details

Date Published: 20 February 2009
PDF: 9 pages
Proc. SPIE 7171, Multimodal Biomedical Imaging IV, 71710Y (20 February 2009); doi: 10.1117/12.809648
Show Author Affiliations
Zbigniew Kulas, Wroclaw Univ. of Technology (Poland)
Elżbieta Bereś - Pawlik, Wroclaw Univ. of Technology (Poland)
Jarosław Wierzbicki, Wroclaw Medical Univ. (Poland)


Published in SPIE Proceedings Vol. 7171:
Multimodal Biomedical Imaging IV
Fred S. Azar; Xavier Intes, Editor(s)

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