Research Of MRE Reconstruction Algorithm Based On Frequency And Alegebraic Inversion Of The Differential Equation

Magnetic resonance elastography (Magnetic Resonance Elastography, MRE) is a kind of new and noninvasive imaging method using magnetic resonance imaging (MRI).It can displays and quantify the elasticity of tissue. It is a mechanized and quantitative mean of traditional palpation with objective and high resolution,and that it has no diagnosis site constraints.MRE image expresses the biomechanical properties parameters of tissue, it can detects the produced particle displacement when the tissue is worked by the external incentive mechanical waves. Now some people have put forward various algorithms to determine elastic properties of the object, one of the challenging problems that MRE faces in the reconstruction of shear modulus image is how to reduce noise and maintain a relatively high contrast. So in this paper, we focus on the study of magnetic resonance elastography reconstruction algorithms.This thesis introduces the elastic graph reconstruction algorithm based on local frequency estimation, it has a variety of implementation models whose traditional realization method is the Gauss filter of dual band width. This paper uses a new filter for local frequency estimation which is logarithmic normal orthogonal wavelet, this is also an innovation of the paper, we will implement the new and traditional methods using Matlab platform for analysis and comparison which shows that the elastic graph resolution using logarithmic normal orthogonal wavelet is better than traditional method. Then this paper also introduces the magnetic resonance elastography reconstruction algorithm based on algebraic inversion of the differential equation, its calculation requires smoothing and two order differential for phase shift data. In order to achieve the above two requirements, we use Savitzky-Golay filter to realize which is a very practical and good filter for denoising. The algebraic inversion of the differential equation algorithm and local frequency estimation algorithm are compared. Finally the paper simply introduces another method about the reconstruction of magnetic resonance elastography that is shear modules decomposition method. Magnetic resonance elastography reconstruction algorithms proposed in this paper are applied to the phantom and human liver, elastic graph of them were analyzed.