Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging modality, that measures diffusion of water in tissues like the human brain. The package contains R-functions to process diffusion-weighted data. The functionality includes diffusion tensor imaging (DTI), structural adaptive smoothing in in case of (DTI) (K. Tabelow, J. Polzehl, V. Spokoiny, and H.U. Voss, Diffusion Tensor Imaging: Structural Adaptive Smoothing, Neuroimage 39(4), 1763-1773 (2008)), modeling for high angular resolution diffusion weighted imaging (HARDI) using Q-ball-reconstruction and tensor mixture models and a streamline fiber tracking for tensor and tensor mixture models. The package provides functionality to manipulate and visualize results in 2D and 3D.
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References in zbMATH (referenced in 2 articles )
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- Carmichael, Owen; Chen, Jun; Paul, Debashis; Peng, Jie: Diffusion tensor smoothing through weighted Karcher means (2013)
- Yu, Tao; Zhang, Chunming; Alexander, Andrew L.; Davidson, Richard J.: Local tests for identifying anisotropic diffusion areas in human brain with DTI (2013)