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Accelerate Quantitative Clinical Neuroimaging Analysis with AI: Steps Toward Personalized Disease Progression Monitoring in Clinical Neurology
Tim Wang, Sydney Neuroimaging Analysis Centre
GTC 2020
Quantitative neuroimaging analysis can further extract critical information from diagnostic imaging. For instance, brain-volume change has been considered as a critical biomarker in neurodegenerative disease progression. Instead of describing the brain shrinking process as "moderate" or "severe" through visual inspection, now we can, with computing, precisely measure the brain-tissue loss at the scale of 0.1% with conventional MRI scans. However, precision and accuracy of the analysis often require an expert level of quality control, usually carried out by certified imaging analysts at dedicated imaging reading centers. Deep learning and GPU acceleration make it possible to transfer complex and sophisticated analysis into fully automated assessment in daily clinics. We'll share views from both imaging scientists and clinicians on how AI is accelerating clinical imaging quantitative biomarker research.