Estimating intravoxel fiber architecture using constrained compressed sensing combined with multitensor adaptive smoothing

Abstract

In diffusion magnetic resonance imaging dMRI, the accuracy of fiber tracking and analysis depends directly on that of intravoxel fiber architecture reconstruction. Several methods have been proposed that estimate intravoxel fiber architecture using low angular resolution acquisitions owing to their shorter acquisition time and relatively low b-values. But these methods are highly sensitive to noise. We propose an approach to estimating intravoxel fiber architecture in low angular resolution dMRI. The method consists in using a constrained compressed sensing CCS method, also known as crossing fiber angular resolution of intravoxel architecture CFARI technique, in combination with multitensor adaptive smoothing in which a diffusion-weighted DW image smoothing scheme is constructed according to the properties of the multitensor field estimated using CFARI. The results on synthetic, physical phantom and real brain DW images show that the proposed method is able to better resolve fiber architectures while correctly preserving image edge information, which provides a new tool for investigating the microstructures of biological tissues and for fiber tractography. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 285-296, 2015