Enforcing necessary non-negativity constraints for common diffusion MRI models using sum of squares programming

Enforcing necessary non-negativity constraints for common diffusion MRI models using sum of squares programming

In this work we investigate the use of sum of squares constraints for various diffusion-weighted MRI models, with a goal of enforcing strict, global non-negativity of the diffusion propagator. We formulate such constraints for the mean apparent propagator model and for spherical deconvolution, guara...

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Bibliographic Details
Main Authors: Tom Dela Haije, Evren Özarslan, Aasa Feragen
Format: Article
Language:English
Published: Elsevier 2020-04-01
Series:NeuroImage
Subjects:
Constrained optimization
Cumulant expansion
Diffusion MRI
Diffusional kurtosis imaging
Diffusion tensor imaging
Mean apparent propagator
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811919309966

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http://www.sciencedirect.com/science/article/pii/S1053811919309966

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