Sparse deconvolution of higher order tensor for fiber orientation distribution estimation
作者：
Highlights：
• We model a regularization of HOT with an l1 penalization not on coefficient vector but directly on the FOD.
• A weighted regularization scheme is developed to iteratively solve the problem.
• Our method allows HOTs to obtain increasingly clean and sharp FOD with very higher order tensors.
• The method appears to be less spurious peaks and more coherence across neighboring FODs.
摘要
Highlights•We model a regularization of HOT with an l1 penalization not on coefficient vector but directly on the FOD.•A weighted regularization scheme is developed to iteratively solve the problem.•Our method allows HOTs to obtain increasingly clean and sharp FOD with very higher order tensors.•The method appears to be less spurious peaks and more coherence across neighboring FODs.
论文关键词：Diffusion magnetic resonance imaging,Fiber orientation distribution,Higher order tensor,Spherical deconvolution,Sparse approximation
论文评审过程：Received 7 January 2015, Revised 10 August 2015, Accepted 2 September 2015, Available online 15 September 2015, Version of Record 14 November 2015.
论文官网地址：https://doi.org/10.1016/j.artmed.2015.09.004
