Estimating intravoxel fiber architecture using constrained compressed sensing combined with multitensor adaptive smoothing. Issue 4 (December 2015)

• Record Type: Journal Article
• Authors: Chu, Chun‐Yu; Huang, Jian‐Ping; Sun, Chang‐Yu; Zhang, Yan‐Li; Liu, Wan‐Yu; Zhu, Yue‐Min
• Is Part Of: International journal of imaging systems and technology. Volume 25:Issue 4(2015:Dec.)
• Page Start: 285
• Page End: 296
• Publication Date: 2015-12
• Subjects: constrained compressed sensing -- diffusion weighted images -- intravoxel fiber architecture -- low angular resolution diffusion -- multitensor; Imaging systems -- Periodicals; Image processing -- Periodicals; 621.367
• DOI: 10.1002/ima.22148
• Languages: English
• ISSNs: 0899-9457

Abstract

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