Detection of diagnostic clues in statistical histometry

Abstract

Examples are given of the detection of diagnostic clues in quantitative cytology and histopathology by statistical testing, such as may be applied in image analytical procedures. Schematic and other examples are presented of the visual images analyzed by each procedure, whose limits are also discussed. The situations analyzed include increased cellularity, differences in nuclear placement patterns, uniformity of displacement, variance in nuclear diameters and chaincode variance of nuclear placement. A specific model is presented for describing or generating a series of dependent observations representing nuclear placement, based on the Box-Jenkins (ARIMA) models for decomposing a spatial or temporal series into several components. This model describes the statistical observations that are random samples from the series. Finally, one graphic example is given in which visual inspection more readily ascertains an alteration than does statistical analysis of a modest-sized sample.