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. The project leverages 3D deep learning, including CNNs and Vision Transformers, to support accurate analysis.
Applicants should have a strong background in mammalian gametogenesis and reproductive biology, with experience in CT analysis of soft tissues.
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📌 AI-Driven Follicle Detection in Murine Nano-CT Images (Roma)
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📍 Roma
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