OoCount: A Machine-Learning Based Approach to Mouse Ovarian Follicle Counting and Classification

Experimental Methods Webinar Series

The number and distribution of ovarian follicles in each growth stage provides a reliable readout of ovarian health and function. During this webinar, we will provide step-by-step instructions to apply and customize OoCount. OoCount is a high-throughput, open-source method for automatic oocyte segmentation and classification from fluorescent 3D images of whole mouse ovaries using a deep-learning convolutional neural network (CNN) based approach.


Jennifer McKey, PhD, University of Colorado Anschutz Medical Campus

Jen McKey is a developmental and reproductive biologist at the University of Colorado. Jen grew up in France and received her undergraduate and graduate training at the University of Montpellier. Her thesis work focused on development of the gastric smooth muscle using the chicken embryo as a model organism. After graduating with a PhD in Developmental Biology, she joined the laboratory of Blanche Capel at Duke University Medical Center in North Carolina. Jen’s postdoctoral work established an integrated framework for the study of the mouse ovary in its native context, revealed the dynamic morphogenesis of the perinatal ovary, and raised the question of how external forces and surrounding tissues affect ovary morphogenesis and the establishment of ovarian subdomains. Jen started her independent lab in the section of Developmental Biology of the department of Pediatrics at The University of Colorado Anschutz Medical Campus in January 2023. Research in her lab focuses on integrating ovary morphogenesis with ovarian differentiation, with the goal of uncovering novel fetal and perinatal determinants of female fertility and reproductive longevity. 

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