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SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry.
Iglesias, Juan E; Billot, Benjamin; Balbastre, Yaël; Magdamo, Colin; Arnold, Steven E; Das, Sudeshna; Edlow, Brian L; Alexander, Daniel C; Golland, Polina; Fischl, Bruce.
Affiliation
  • Iglesias JE; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Billot B; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Balbastre Y; Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Magdamo C; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Arnold SE; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Das S; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Edlow BL; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Alexander DC; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Golland P; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Fischl B; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Sci Adv ; 9(5): eadd3607, 2023 02 03.
Article in En | MEDLINE | ID: mdl-36724222
ABSTRACT
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Neuroimaging Type of study: Observational_studies Limits: Humans Language: En Journal: Sci Adv Year: 2023 Type: Article Affiliation country: United States
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Neuroimaging Type of study: Observational_studies Limits: Humans Language: En Journal: Sci Adv Year: 2023 Type: Article Affiliation country: United States