Statistical pattern recognition algorithms for autofluorescence imaging

Zbigniew Kulas; Elżbieta Bereś - Pawlik; Jarosław Wierzbicki

doi:10.1117/12.809648

20 February 2009 Statistical pattern recognition algorithms for autofluorescence imaging

Zbigniew Kulas, Elżbieta Bereś - Pawlik, Jarosław Wierzbicki

Author Affiliations +

Proceedings Volume 7171, Multimodal Biomedical Imaging IV; 71710Y (2009) https://doi.org/10.1117/12.809648
Event: SPIE BiOS, 2009, San Jose, California, United States

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.

Citation Download Citation

Zbigniew Kulas, Elżbieta Bereś - Pawlik, and Jarosław Wierzbicki "Statistical pattern recognition algorithms for autofluorescence imaging", Proc. SPIE 7171, Multimodal Biomedical Imaging IV, 71710Y (20 February 2009); https://doi.org/10.1117/12.809648

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