Abstract
Magnetic resonance elastography (MRE) is an imaging modality capable of visualizing the elastic properties of an object using magnetic resonance imaging (MRI) measurements of transverse acoustic strain waves induced in the object by a harmonically oscillating mechanical vibration. Various algorithms have been designed to determine the mechanical properties of the object under the assumptions of linear elasticity, isotropic and local homogeneity. One of the challenging problems in MRE is to reduce the noise effects and to maintain contrast in the reconstructed shear modulus images. In this paper, we propose a new algorithm designed to reduce the degree of noise amplification in the reconstructed shear modulus images without the assumption of local homogeneity. Investigating the relation between the measured displacement data and the stress wave vector, the proposed algorithm uses an iterative reconstruction formula based on a decomposition of the stress wave vector. Numerical simulation experiments and real experiments with agarose gel phantoms and human liver data demonstrate that the proposed algorithm is more robust to noise compared to standard inversion algorithms and stably determines the shear modulus.
Original language | English |
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Article number | 5265288 |
Pages (from-to) | 1526-1533 |
Number of pages | 8 |
Journal | IEEE Transactions on Medical Imaging |
Volume | 28 |
Issue number | 10 |
DOIs | |
Publication status | Published - 2009 Oct |
Bibliographical note
Funding Information:Manuscript received March 08, 2009; revised March 18, 2009. Current version published September 25, 2009. The work of O. I. Kwon was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD) (KRF-2005-201-C00004), This work was supported in part by the SRC/ERC program of MOST/KOSEF (R11-2002-103) and in part by the National Institutes of Health under Grant EB001981 and Grant NIH-C06-RR018898. Asterisk indicates corresponding author. *O. I. Kwon is with the Department of Mathematics, Konkuk University, Seoul 143–701, Korea (e-mail: oikwon@konkuk.ac.kr).
All Science Journal Classification (ASJC) codes
- Software
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering