Decomposition of Displacement Field into the Irrotational and Solenoidal Component Using Fast Fourier Transform

Reza Bahrami  Gorji; Mohammad  Mohammadi; Bahador  Makkiabadi

doi:10.18502/fbt.v10i4.13729

Reza Bahrami Gorji Department of Medical Physics and Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
Mohammad Mohammadi Department of Medical Physics and Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
Bahador Makkiabadi Department of Medical Physics and Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

DOI: https://doi.org/10.18502/fbt.v10i4.13729

Keywords: Helmholtz Decomposition; Fourier Transform; Vector Field; Longitudinal Waves; Transverse Waves.

Abstract

Purpose: A new code based on Helmholtz decomposition is presented to separate longitudinal (pressure) and transverse (shear) components of a mixed wave field. This algorithm will help isolate shear or pressure components of an elastic wave to further concentrate on each specific wave and its physical characteristics, particularly in medical imaging instrument development and image processing techniques.

Materials and Methods: Using the combination of Fourier transform and Helmholtz decomposition, first, the mathematical basis of the work is prepared. After reaching a usable formula, this basis is embedded in the Code written in MATLAB program. Then, various test data containing shear and pressure waves were created and fed to the Code to evaluate its ability to decompose the displacements into the shear and pressure waves.

Results: This new algorithm successfully isolated the transverse and longitudinal wavefront of the mixed wavefield. The Code demonstrated 100% accuracy for separating the shear wave and more than 99% for the pressure wave. Moreover, the background noise was kept under 0.03% in every step.

Conclusion: The results show that using Helmholtz decomposition in Fourier space on 3D data can help decompose a displacement field into its irrotational and solenoidal components with high accuracy. A weak dependency on wave thickness and contrast was observed, but the algorithm's accuracy never fell below 99%.