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A unified framework for estimating diffusion tensors of any order with symmetric positive-definite constraints

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2 Author(s)
Barmpoutis, A. ; Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA ; Vemuri, B.C.

Cartesian tensors of various orders have been employed for either modeling the diffusivity or the orientation distribution function in Diffusion-Weighted MRI datasets. In both cases, the estimated tensors have to be positive-definite since they model positive-valued functions. In this paper we present a novel unified framework for estimating positive-definite tensors of any order, in contrast to the existing methods in literature, which are either order-specific or fail to handle the positive-definite property. The proposed framework employs a homogeneous polynomial parametrization that covers the full space of any order positive-definite tensors and explicitly imposes the positive-definite constraint on the estimated tensors. We show that this parametrization leads to a linear system that is solved using the non-negative least squares technique. The framework is demonstrated using synthetic and real data from an excised rat hippocampus.

Published in:

Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on

Date of Conference:

14-17 April 2010

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