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Medical Image Analysis //

Multimodal Data Fusion for Brain Connectivity Analysis

Despite enormous strides in  our understanding of  neural physiology, the transition from cellular and subcellular functional variability to variations in  human behavior is poorly  understood.  Current evidence ties this transition to complex interactions  within brain functional networks. These networks are not easy to estimate from the data due to their dynamic  nature. However,  accurately characterizing them  is of the  uttermost  importance  for  diagnosis and  prediction  of  mental disorders at their early stages (e.g. schizophrenia).  This project is aiming to  improve estimation of  brain functional networks  by taking advantage  of  the  complementary  nature of  multiple  brain  imaging modalities. The main  application is in the study  of mental disorders linked to brain network dysfunction (schizophrenia, Alzheimer's, ADHD, bipolar disorder and others).

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