Pediatric Neuroimaging

Special Session 6

Organizers

Anqi Qiu, National University of Singapore; James Gee, University of Pennsylvania and University of Electronic Science and Technology of China

 Speakers

  • Tianzi Jiang, (Professor of National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences)
  • Simon Warfield (Thorne Griscom Chair and Professor of Radiology, Harvard Medical School, Boston Children’s Hospital)
  • Andrew Zalesky (Professor of Psychiatry, Electrical and Electronic Engineering, the University of Melbourne)
  • Tonya White (Associate Professor, Erasmus University Rotterdam)

Keywords:

Brain connectome, brain imaging, spatio-temporal brain analysis, brain network.

Abstract:

The brain develops rapidly through neurogenesis, axonal and dendritic growth, synaptogenesis, cell death, synaptic pruning, myelination, and gliogenesis. These ontogenetic events happen at different times and build on each other. Small perturbations in these processes can introduce long-term effects on both brain structure and function. Hence, it is crucial to gain insight into the brain’s developmental trajectory in normal growth and in neurodevelopmental disorders. Imaging has been revolutionary in enabling in vivo characterization of the pediatric brain and its development. This special session will feature presentations from leading investigators in the field covering topics ranging from imaging technologies and techniques for pediatric neuroimaging to image processing techniques specialized to the infant brain, to spatio-temporal analysis methods for characterizing brain anatomical and functional networks, and to statistical approaches for modeling early brain growth and detecting changes from normal development.

Other special sessions

Bio-inspired data mining and deep learning in biomedical image processing
Medical Imaging in Stroke
Breast Image Analysis
From Lab Technology to Clinical Applications: Latest Advances in Functional Near Infrared Spectroscopy (fNIRS)
Tele-Health: Assessing health with real-world constraints