AI-Driven Follicle Detection in Murine Nano-CT Images
Pubblicato il 09-08-2026 - Italian Ministry of Education, University and Research in Italia
Università di Pavia collaborates with engineers to develop an AI tool that automatically detects and localizes ovarian follicles from nanoCT imaging datasets, aiming to automate classification and improve scalability.
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The project leverages 3D deep learning, including CNNs and Vision Transformers, to support accurate analysis. xysqume
Applicants should have a strong background in mammalian gametogenesis and reproductive biology, with experience in CT analysis of soft tissues.
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