ML Researcher’s Guide to Open Brain Imaging Data

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1. ML RESEARCHER’S GUIDETO OPEN BRAIN IMAGING DATA Chris Gorgolewski @ChrisFiloG Stanford Center for Reproducible Neuroscience 2. WHY BRAIN DATA IS IMPORTANT? 3. The…

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  • 1. ML RESEARCHER’S GUIDETO OPEN BRAIN IMAGING DATA Chris Gorgolewski @ChrisFiloG Stanford Center for Reproducible Neuroscience
  • 2. WHY BRAIN DATA IS IMPORTANT?
  • 3. The cost of mental health
  • 4. The end of radiology? “People should stop training radiologists now” Jeff Hinton, 2016 https://www.youtube.com/watch?v=2HMPRXstSvQ
  • 5. algorithms + data = breakthroughs https://www.kdnuggets.com/2016/05/datasets-over-algorithms.html
  • 6. THE NATURE OF THE DATA
  • 7. 3D cubes of values
  • 8. Structural scans ■ Single 3D image ■ “high resolution“ 256x256x160 ■ Different histogram profiles
  • 9. Diffusion scans ■ Series (x70-90) of 3D images – Each with slightly different contrast ■ Good for looking at white matter – axons – “wiring of the brain”
  • 10. Functional scans ■ Long series of seemingly identical images ■ Low resolution 64x64x64x600 ■ Sensitive to tiny differences in blood flow ■ Can detect which parts of the brain are “active” at any given time ■ Great for studying cognition
  • 11. EXISTING RESOURCES
  • 12. Brain tumors T1 T2 diffusion functional Pernet dataset • 22 participants • T1,T2, diffusion, functional • Demographics • Photographs from surgeries https://www.nature.com/articles/sdata20163
  • 13. Brain tumors BRATS • 30 participants • T1,T2, FLAIR, and post- GadoliniumT1 • Segmented • Designed for a MICCAI competition http://www2.imm.dtu.dk/projects/BRATS2012/data.html
  • 14. Brain tumors BITE: Brain Images of Tumors for Evaluation database • 15 participants • T1-weighted MR with gadolinium • Ultrasound images • Pre and post resection http://nist.mni.mcgill.ca/?page_id=672
  • 15. Stroke ATLAS (Anatomical Tracings of LesionsAfter Stroke) • 304 participants • T1-weighted • Manually segmented https://www.nature.com/articles/sdata201811
  • 16. Alzheimer’s Disease Neuroimaging Initiative (ADNI) ■ T1,T2, functional, diffucion and PET data ■ Longitudinal ■ ~800 participants http://adni.loni.usc.edu/
  • 17. Autism Brain Imaging Data Exchange (ABIDE) ■ 2156 participants ■ T1 and functional data ■ Phenotypic data http://fcon_1000.projects.nitrc.org/indi/abide
  • 18. Attention Deficit Hyperactivity Disorder 200 ■ 776 participants ■ T1w and functional ■ Part of a competition http://fcon_1000.projects.nitrc.org/indi/adhd200/
  • 19. OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer’s Disease ■ 1098 participants – 609 cognitively normal adults – 489 individuals at various stages of cognitive decline ■ T1w,T2w, FLAIR, ASL, SWI, time of flight, resting-state BOLD, and DTI sequences http://www.oasis-brains.org
  • 20. SchizConnect ■ 1302 participants ■ Aggregated data across sites ■ T1,T2, functional http://schizconnect.org/
  • 21. Transfer learning Catalog of healthy structural brain scans: github.com/cMadan/openMorph ~100,000T1 scans
  • 22. Brainhack Global San Francisco ■ San Francisco, CA, USA ■ May 03-05, 2018 ■ https://sfbrainhack.github.io/ ■ Friendly vibes, local experts willing to collaborate
  • 23. Got stuck? http://neurostars.org open online Q/A community for neuroimaging
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