The aim of this study was (1) to investigate the value of morphometry, (2) to fix a set of parameters suitable for analyzing diagnostic problems, and (3) to create a general strategy for data storage and for user-friendly data management. The intrinsic value of morphometry lies in the fact that in contrast to other morphologic methods, it permits the presentation of findings in the form of numbers. The following set of morphometric parameters, in the broad sense of the term morphometry, is standard in our laboratory: planimetric parameters (shape descriptors), parameters of the gray value histogram (descriptors of the general gray value distribution), texture parameters (descriptors of the correlation between various image segments), invariant moments (descriptors of the size and localization of textural image segments) and densitometric parameters. The introduction of morphometric procedures into the daily routine is facilitated if data registration and evaluation are performed separately. Original data generated by direct measurement are primary or raw data, which are stored as such. In a separate, second step these raw data are used to compare more or less complex morphometric parameters, which are called "secondary data". A system designed for separate data registration and evaluation can easily be adapted to new methodologic developments. For instance, primary data on objects (gray values, coordinates of the contour) measured one time in the past can be reused at any other time for computing new features from these data. This procedure is comparable to the possibilities in immunohistochemical staining: new immunohistochemical stains can be applied to newly prepared sections of old tissue blocks.