Despite all efforts made to develop predictive biomarkers for antiangiogenic therapies, no unambiguous markers have been identified so far. This is due to among others the lack of standardized tests. This study presents an improved microvessel density quantification method in tumor tissue based on stereological principles and using whole-slide images. Vessels in tissue sections of different cancer types were stained for CD31 by an automated and validated immunohistochemical staining method. The stained slides were digitized with a digital slide scanner. Systematic, uniform, random sampling of the regions of interest on the whole-slide images was performed semi-automatically with the previously published applications AutoTag and AutoSnap. Subsequently, an unbiased counting grid was combined with the images generated with these scripts. Up to six independent observers counted microvessels in up to four cancer types: colorectal carcinoma, glioblastoma multiforme, ovarian carcinoma and renal cell carcinoma. At first, inter-observer variability was found to be unacceptable. However, after a series of consensus training sessions and interim statistical analysis, counting rules were modified and inter-observer concordance improved considerably. Every CD31-positive object was counted, with exclusion of suspected CD31-positive monocytes, macrophages and tumor cells. Furthermore, if interconnected, stained objects were considered a single vessel. Ten regions of interest were sufficient for accurate microvessel density measurements. Intra-observer and inter-observer variability were low (intraclass correlation coefficient > 0.7) if the observers were adequately trained.