Open Access
September 2016 Fiber direction estimation, smoothing and tracking in diffusion MRI
Raymond K. W. Wong, Thomas C. M. Lee, Debashis Paul, Jie Peng, Alzheimer’s Disease Neuroimaging Initiative
Ann. Appl. Stat. 10(3): 1137-1156 (September 2016). DOI: 10.1214/15-AOAS880


Diffusion magnetic resonance imaging is an imaging technology designed to probe anatomical architectures of biological samples in an in vivo and noninvasive manner through measuring water diffusion. The contribution of this paper is threefold. First, it proposes a new method to identify and estimate multiple diffusion directions within a voxel through a new and identifiable parametrization of the widely used multi-tensor model. Unlike many existing methods, this method focuses on the estimation of diffusion directions rather than the diffusion tensors. Second, this paper proposes a novel direction smoothing method which greatly improves direction estimation in regions with crossing fibers. This smoothing method is shown to have excellent theoretical and empirical properties. Last, this paper develops a fiber tracking algorithm that can handle multiple directions within a voxel. The overall methodology is illustrated with simulated data and a data set collected for the study of Alzheimer’s disease by the Alzheimer’s Disease Neuroimaging Initiative (ADNI).


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Raymond K. W. Wong. Thomas C. M. Lee. Debashis Paul. Jie Peng. Alzheimer’s Disease Neuroimaging Initiative. "Fiber direction estimation, smoothing and tracking in diffusion MRI." Ann. Appl. Stat. 10 (3) 1137 - 1156, September 2016.


Received: 1 January 2015; Revised: 1 September 2015; Published: September 2016
First available in Project Euclid: 28 September 2016

zbMATH: 06775262
MathSciNet: MR3553220
Digital Object Identifier: 10.1214/15-AOAS880

Keywords: Diffusion tensor imaging , direction smoothing , fiber tracking , multi-tensor model , tractography

Rights: Copyright © 2016 Institute of Mathematical Statistics

Vol.10 • No. 3 • September 2016
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