Human ovarian reserve is defined by the population of nongrowing follicles
(NGFs) in the ovary. Direct estimation of ovarian reserve involves the
identification of NGFs in prepared ovarian tissue. Previous studies involving
human tissue have used hematoxylin and eosin (HE) stain, with NGF populations
estimated by human examination either of tissue under a microscope, or of
images taken of this tissue. In this study we replaced HE with proliferating
cell nuclear antigen (PCNA), and automated the identification and enumeration
of NGFs that appear in the resulting microscopic images. We compared the
automated estimates to those obtained by human experts, with the "gold
standard" taken to be the average of the conservative and liberal estimates by
three human experts. The automated estimates were within 10% of the "gold
standard", for images at both 100x and 200x magnifications. Automated analysis
took longer than human analysis for several hundred images, not allowing for
breaks from analysis needed by humans. Our results both replicate and improve
on those of previous studies involving rodent ovaries, and demonstrate the
viability of large-scale studies of human ovarian reserve using a combination
of immunohistochemistry and computational image analysis techniques.