On High Order Tensor-based Diffusivity Profile Estimation
Paper in proceedings, 2013

Diffusion weighted magnetic resonance imaging (dMRI) is used to measure, in vivo, the self-diffusion of water molecules in biological tissues. High order tensors (HOTs) are used to model the apparent diffusion coefficient (ADC) profile at each voxel from the dMRI data. In this paper we propose: (i) A new method for estimating HOTs from dMRI data based on weighted least squares (WLS) optimization; and (ii) A new expression for computing the fractional anisotropy from a HOT that does not suffer from singularities and spurious zeros. We also present an empirical evaluation of the proposed method relative to the two existing methods based on both synthetic and real human brain dMRI data. The results show that the proposed method yields more accurate estimation than the competing methods.

High order tensor

Z-eigenvalue

ADC profile

Fractional Anisotropy

Weighted least squares

Diffusion-weighted MRI (dMRI)

Author

Mohammad Alipoor

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Irene Yu-Hua Gu

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Andrew Mehnert

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Imaging and Image Analysis

Y Lilja

Sahlgrenska University Hospital

Daniel Nilsson

Sahlgrenska University Hospital

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

1557170X (ISSN)

93-96 6609445

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Signal Processing

Neurology

Radiology, Nuclear Medicine and Medical Imaging

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing

DOI

10.1109/EMBC.2013.6609445

ISBN

978-14-57-70216-7

More information

Latest update

4/17/2018