Practical AI
Seeing beyond the scan in neuroimaging
Apr 30, 2025
Gavin Winston, a Professor at Queen's University and an expert in neuroimaging and AI in healthcare, dives into the fascinating world of epilepsy diagnosis using machine learning. He reveals how MRI data can identify subtle brain abnormalities and discusses the cultural and ethical challenges of integrating AI in clinical settings. The conversation also covers the potential of AI to enhance diagnostic workflows and improve collaboration between radiologists and physicians, shaping a promising future for neuroimaging.
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Quick takeaways
- Machine learning in neuroimaging can identify subtle brain abnormalities and enhance diagnostic accuracy through efficient data analysis.
- Cultural and ethical barriers currently hinder the adoption of AI technologies in healthcare, impacting their integration into medical imaging workflows.
Deep dives
Understanding Neuroimaging Techniques
Neuroimaging encompasses various techniques aimed at examining the structure and function of the brain. Techniques such as MRI, CT scans, and PET scans allow clinicians to identify abnormalities and understand neurological issues. MRI, in particular, provides detailed images that can reveal structural issues linked to conditions like seizures and memory impairments. The field has evolved significantly since the introduction of CT scans in the 1970s, transitioning from exploratory methods to advanced imaging that generates substantial data for analysis.
