Multi-component fiber track modelling of diffusion-weighted magnetic resonance imaging data

Yasser M. Kadah, Inas A. Yassine
2010 Journal of Advanced Research  
In conventional diffusion tensor imaging (DTI) based on magnetic resonance data, each voxel is assumed to contain a single component having diffusion properties that can be fully represented by a single tensor. Even though this assumption can be valid in some cases, the general case involves the mixing of components, resulting in significant deviation from the single tensor model. Hence, a strategy that allows the decomposition of data based on a mixture model has the potential of enhancing the
more » ... diagnostic value of DTI. This project aims to work towards the development and experimental verification of a robust method for solving the problem of multi-component modelling of diffusion tensor imaging data. The new method demonstrates significant error reduction from the single-component model while maintaining practicality for clinical applications, obtaining more accurate Fiber tracking results.
doi:10.1016/j.jare.2010.02.001 fatcat:mk3dixfmr5feljd2or7b7hhifq