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2015 Project-Team Activity Report
ATHENA
Computational Imaging of the Central Nervous System


Field: Digital Health, Biology and Earth

Theme: Computational Neuroscience and Medecine
Keywords:
Computer Science and Digital Science:
  • 3.1.1. - Modeling, representation
  • 3.1.4. - Uncertain data
  • 3.3.3. - Big data analysis
  • 3.4.1. - Supervised learning
  • 3.4.2. - Unsupervised learning
  • 3.4.3. - Reinforcement learning
  • 3.4.4. - Optimization and learning
  • 3.4.5. - Bayesian methods
  • 3.4.7. - Kernel methods
  • 5.1.4. - Brain-computer interfaces, physiological computing
  • 5.2. - Data visualization
  • 5.3.2. - Sparse modeling and image representation
  • 5.3.4. - Registration
  • 5.9.1. - Sampling, acquisition
  • 5.9.2. - Estimation, modeling
  • 5.9.3. - Reconstruction, enhancement
  • 5.9.4. - Signal processing over graphs
  • 5.9.5. - Sparsity-aware processing
  • 5.9.6. - Optimization tools
  • 6.1.1. - Continuous Modeling (PDE, ODE)
  • 6.1.4. - Multiscale modeling
  • 6.1.5. - Multiphysics modeling
  • 6.2.1. - Numerical analysis of PDE and ODE
  • 6.2.3. - Probabilistic methods
  • 6.2.4. - Statistical methods
  • 6.2.6. - Optimization
  • 6.2.8. - Computational geometry and meshes
  • 6.3.1. - Inverse problems
  • 6.3.2. - Data assimilation
  • 6.3.3. - Data processing
  • 6.3.4. - Model reduction
  • 7.8. - Information theory
  • 7.9. - Graph theory
  • 8.2. - Machine learning
  • 8.3. - Signal analysis
Other Research Topics and Application Domains:
  • 1.3.1. - Understanding and simulation of the brain and the nervous system
  • 1.3.2. - Cognitive science
  • 1.4. - Pathologies
  • 2.2.2. - Nervous system and endocrinology
  • 2.2.6. - Neurodegenerative diseases
  • 2.5.1. - Sensorimotor disabilities
  • 2.5.2. - Cognitive disabilities
  • 2.5.3. - Assistance for elderly
  • 2.6.1. - Brain imaging
  • 2.6.2. - Cardiac imaging
  • 2.7.1. - Surgical devices