Big Brains How Full-Body MRIs Could Predict Your Long-Term Health, with Daniel Sodickson
Oct 30, 2025
In this enlightening discussion, Daniel Sodickson, a leading MRI researcher and professor at NYU, dives into the transformative power of full-body MRIs for predictive health. He explores how these advanced imaging techniques can change medicine from reactive to proactive. Sodickson discusses the intersection of AI and imaging, highlighting its potential to enhance diagnosis while preserving the critical role of radiologists. The conversation also touches on privacy concerns and the ethical implications of widespread imaging technology for health monitoring.
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Imaging As Predictive Medicine
- Full-body MRI plus AI can shift medicine from reactive to predictive by tracking individuals over time.
- Using prior context reduces false positives and improves meaningful detection.
Parallel Imaging Origin Story
- Sodickson described inventing parallel imaging to speed MRI by collecting multiple projections at once.
- That development came from needing faster cardiac imaging for a moving heart.
Pre-Compression Speeds MRI
- Compressed sensing gathers a pre-compressed representation to avoid collecting unnecessary data.
- It accelerates imaging by reconstructing full images from fewer measurements.
