We used a novel approach to estimate the densities of dendrites and spines in this study. Most morphometric studies of dendrites and spines in experimental animals and in human postmortem brain tissues have used Golgi staining with Scholl analyses or other labor-intensive approaches to estimate the number, lengths, and patterns of labeled processes and objects of interest in comparatively small samples. In the present study, we used a more high-throughput approach consisting of immunohistochemical labeling in thin sections for proteins that are highly enriched in the neuronal compartments of interest, ie, MAP2 in dendrites and synaptopodin in dendritic spines. For quantitation, we used semiautomated algorithmic image analysis to segment and estimate the densities of neuronal profiles, dendrites, and spines. There are relative advantages and disadvantages to each approach. Morphological detail with Golgi staining can be exquisite, and much of the full extent of a given neuron's dendritic tree can be measured. However, Golgi staining labels the somata, axons, dendrites, and spines of only some neurons, and which neurons it labels is unpredictable. Finally, Golgi staining is technically lengthy and challenging, variable from case to case, and does not lend itself well to larger-scale studies. In contrast, immunohistochemistry with antibodies directed at MAP2 and synaptopodin respectively label all dendrites and spines that express those proteins, is technically more uniform and robust, can be conducted in variously fixed and processed tissues, and is suitable for high-throughput analysis of relatively large samples. On the other hand, limitations of this method can include variability in enzymatic reaction product contrast and resolution, especially for dense and overlapping dendrites and spines, different shrinkages of tissue with heat-induced or other epitope retrieval methods, and vulnerability to split-object artifact inherent in 2-dimensional quantitation. We attempted to attenuate these limitations by using computer-assisted algorithmic size, shape, optical density, and pixel contiguity filtering to delineate and then measure standard 1-pixel-wide lengths of skeletonized dendrites or count segmented synaptopodin-immunoreactive puncta. These methods allowed for more reliable measurement, although they precluded measurement of certain data that may be informative, such as thickness, shape, or staining intensity. We also applied a correction factor to moderate split-cell artifact bias in our 2-dimensional neuron density determination. Finally, we “normalized” our dendrite and spine densities to the densities of neurons in CA3, thus eliminating the potential confounder of variable tissue shrinkage.