Designing a data format for state-of-the-art multi-modal MRI analysis
A unique strength of magnetic resonance imaging (MRI) in neuroscience is its ability to generate images containing different contrasts that provide unique insight into both brain anatomy and connectivity.
State-of-the-art analyses of such complex data are typically tailored to the particular strengths of each modality, as well as the complex geometric structure of the brain. This can however limit the extent to which multiple such modalities can be used in a single analysis, since they all use different strategies for representing and analysing the data. The goal of this project is to define a new standardised format for storage and analysis of advanced neuroimaging data, encompassing state-of-the-art technological advancements across multiple modalities.
The brain is a complex structure in terms of both structure and function. There are many modalities of MRI that can be used to interrogate its various features. However, the strategies used for storing and analysing such data are typically tailored to the specific features that can be interrogated using each modality. This can preclude using multiple such sources of data within comprehensive analyses.
The goal of this project is to define a new standardised format for storage and analysis of advanced neuroimaging data, encompassing state-of-the-art technological advancements across multiple modalities. This will facilitate the use of many such modalities in conjunction with one another, enabling higher-order analyses of multi-modal MRI data in neuroscience to interrogate higher-level hypotheses regarding brain structure and function.
Additionally, a natural consequence of the intrinsic design of this format is that data will be intrinsically applicable for use in artificial intelligence systems.