Gastric cancer often appears without preliminary symptoms that could be detected and recognized at earlystages. Its diagnostic is sometime provided based on photodynamic techniques, although the latter are restrictedby quite poor tumor selectivity. Due to this, additional experimental and data processing tools are required toimprove diagnostic abilities. In this study we analyze how complexity measures can detect early changes in thenormal gastric microcirculation. We apply a recently developed approach based on the multiscale entropy andshow that the estimated measures of SampEn related to distinct ranges of scales enable the detection of earlygastric cancer that is in accordance with the results of histological analysis.
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