The nucleator is a well-established manual stereological method of estimating mean cell volume from observations on random cell sections through reference points of the cells. In this paper, we present an automated version of the nucleator that uses automatic segmentation of the boundaries of the cell sections. An expert supervises the process. If the segmentation is judged to be satisfactory, an estimate of the cell volume is calculated automatically on the basis of the whole cell section. In the remaining cases, the expert intervenes and uses the classical nucleator. The resulting estimator is called the semi-automatic nucleator. In the present paper, we study the statistical properties of the semi-automatic nucleator. Formulae for the bias and mean square error are derived. The semi-automatic nucleator may have a small bias but will still in most cases be more efficient than the classical nucleator. Procedures for estimating bias and mean square error (MSE) from a pilot study are provided. The application of the semi-automatic nucleator is illustrated in a study of somatostatin positive inhibitory interneurons which were genetically labeled with green fluorescent protein (GFP). It is found in this study that the number of cells needed for obtaining, for instance, a 5% precision of the estimate of mean cell volume is 150 and 189 for the semi-automatic and the classical nucleator, respectively. Taking into account that the time spent analyzing one cell is shorter for the semi-automatic nucleator than for the classical nucleator, the semi-automatic nucleator is superior to the classical nucleator.

Key words: computerized image analysis, local stereology, nucleator, volume