Functional recovery after stroke is associated with structural reorganization of neural networks around the lesion. However, little is known about the exact mechanisms and temporal evolution of this remodeling. Diffusion tensor imaging depicts in vivo structure of gray and white matter, but it has disadvantages limiting its use in the study of these processes. In an effort to address these, several new diffusion magnetic resonance imaging schemes have been developed in the current decade. Moreover, these techniques promise to reveal extra information about intravoxel diffusion, which could provide better characterization of neural tissue and more insight into brain disease. However, these improvements come at the price of hardware requirements, scan duration and uncertainty about the required assumptions as well as accuracy of these methods. This thesis provides some background on diffusion imaging and its use in stroke before discussing the advantages, drawbacks and validity of novel methods
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