As treatment options for neurological diseases expand by number, gradation, and sophistication, it is imperative for neuroanatomical studies to use quantitative and objective methods, so that anatomic biomarkers can be used to further refine approaches and procedures. We present the results of a semi-automatic process that measures features of neural populations within the posterior cingulate cortex (PCC), a region known for its high metabolic rate, being part of the default mode network, and implicated in various degenerative diseases; including Parkinsonism, Alzheimer’s, and Depression. For the first step we have analyzed and objectively bounded a subregion, Brodmann Area (BA) 23 ventral (BA23v) in ten hemispheres from five adult human brains. BA23v abuts retrosplenial area BA30 on its lateral and posterior border and BA23 dorsal on its dorsal and anterior borders. The longitudinal fissure is medial. The algorithm derives ‘grey-level index (GLI) maps’ by creating binary images from a silver, Nissl-like stain. Following this, it measures the volume density of cells along vertical strips from the border between layers I and II to the white matter border. The resulting profiles provide ten parameters (including mean GLI for all layers, their skewness, kurtosis and first derivatives) that are iteratively measured and then compared using sets of sliding windows. The comparisons produce a statistically testable definition of borders. The algorithm has been evaluated in many different types of cortices and is used to define many cortical regions. We found the border between BA30 and BA23v to agree with descriptive observations of the existence of a narrow, but unbroken layer IV and the presence of large neuronal cell bodies in layer V. This border region showed a small range of spatial variation whereas the border between BA23v and BA23d, defined descriptively by differences in perikaryal sizes, had a larger spatial range.