This episode delves into advancements in intraoperative visualization for skull base surgery. We discuss the feasibility study titled 'Real-time intraoperative depth estimation in transsphenoidal surgery using deep learning,' published in the Journal of Clinical Neuroscience in 2026. The abstract highlights how deep learning can generate three-dimensional depth perception from standard endoscopic video feeds, addressing a critical limitation in transsphenoidal approaches for pituitary adenomas and other lesions. This technology promises to improve surgeon orientation and potentially enhance patient outcomes by overcoming the challenges of two-dimensional imaging. This discussion is for informational purposes and does not constitute medical advice.