The use of a computational approach in histological analysis can help in the acquisition and interpretation of results. In this work, we present a computational method to automate the morphometrical protocol proposed by Ewald R. Weibel in 1966. The method proposed here was based on the use of widely known image processing algorithms aiming to identify regions of interest (i.e. image segmentation, thresholding and flood fill). The method also uses mathematical morphology, such as the opening operator to filter the noise left by the thresholding. As a contribution of this work, we also created a software tool, named AutoGrid, to support reasearchers of biology labs apply the method. The proposal was evaluated on a set of images taken from rat prostate. In this scenario, we extracted data to perform histological analysis both using the software tool and following the manual protocol. When the tool was used (i.e. semi-automatic mode), the user was asked to perform a little manual intervention, and the most time consuming and tiring parts of the process runs automatically. Finally, the computational approach presented a faster (i.e. 45% less time) and less monotonous histological analysis, with statistically equivalent results to those obtained on the manual mode.