SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry.
Juan Eugenio IglesiasBenjamin BillotYael BalbastreColin MagdamoSteven E ArnoldSudeshna DasBrian L EdlowDaniel C AlexanderPolina GollandBruce FischlPublished in: Science advances (2023)
Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in hospitals across the world. These have the potential to revolutionize our understanding of many neurological diseases, but their morphometric analysis has not yet been possible due to their anisotropic resolution. We present an artificial intelligence technique, "SynthSR," that takes clinical brain MRI scans with any MR contrast (T1, T2, etc.), orientation (axial/coronal/sagittal), and resolution and turns them into high-resolution T1 scans that are usable by virtually all existing human neuroimaging tools. We present results on segmentation, registration, and atlasing of >10,000 scans of controls and patients with brain tumors, strokes, and Alzheimer's disease. SynthSR yields morphometric results that are very highly correlated with what one would have obtained with high-resolution T1 scans. SynthSR allows sample sizes that have the potential to overcome the power limitations of prospective research studies and shed new light on the healthy and diseased human brain.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- computed tomography
- high resolution
- artificial intelligence
- magnetic resonance
- deep learning
- diffusion weighted imaging
- resting state
- white matter
- healthcare
- machine learning
- dual energy
- cerebral ischemia
- mass spectrometry
- big data
- endothelial cells
- functional connectivity
- convolutional neural network
- human health
- climate change
- single molecule
- sensitive detection
- living cells