The researchers aim to bridge the gap in knowledge regarding the link between female brain health and sex hormone fluctuations. They developed tools that quantify 3D shape changes in the brain during these fluctuations. They propose approximation schemes that accelerate geodesic regression on shape spaces of 3D discrete surfaces, proving to be both fast and accurate. They apply the method to real brain shape data, providing the first characterization of how the female hippocampus changes shape during the menstrual cycle in relation to progesterone levels. This research offers a new perspective in bio-medicine and computer vision fields.
Publication date: 29 Sep 2023
Project Page: Not provided
Paper: https://arxiv.org/pdf/2309.16662
