Higher dimensional homodyne filtering for suppression of incidental phase artifacts in multichannel MRI

01/14/2015
by   Joseph Suresh Paul, et al.
0

The aim of this paper is to introduce procedural steps for extension of the 1D homodyne phase correction for k-space truncation in all gradient encoding directions. Compared to the existing method applied to 2D partial k-space, signal losses introduced by the phase correction filter is observed to be minimal for the extended approach. In addition, the modified form of phase correction mitigates Incidental Phase Artifacts (IPA) due to truncation. For parallel imaging with undersampling along phase encode direction, the extended homodyne filtering is shown to be effective for minimizing these artifacts when each of the channel k-spaces are truncated along both phase and frequency encode directions. This is illustrated with 2D partial k-space for flow compensated multichannel Susceptibility Weighted Imaging (SWI). Extension of our method to 3D partial k-space shows improved reconstruction of flow information in phase contrast angiography.

READ FULL TEXT

page 21

page 22

page 27

page 29

page 30

page 31

page 32

page 33

research
09/15/2017

General Phase Regularized Reconstruction using Phase Cycling

Purpose: To develop a general phase regularized image reconstruction met...
research
06/13/2021

Is Perfect Filtering Enough Leading to Perfect Phase Correction for dMRI data?

Being complex-valued and low in signal-to-noise ratios, magnitude-based ...
research
02/15/2022

Phase Vocoder Done Right

The phase vocoder (PV) is a widely spread technique for processing audio...
research
06/01/2018

k-Space Deep Learning for Reference-free EPI Ghost Correction

Nyquist ghost artifacts in EPI images are originated from phase mismatch...
research
10/29/2016

A MAP-MRF filter for phase-sensitive coil combination in autocalibrating partially parallel susceptibility weighted MRI

A statistical approach for combination of channel phases is developed fo...
research
05/16/2020

Analytic Signal Phase in N-D by Linear Symmetry Tensor–fingerprint modeling

We reveal that the Analytic Signal phase, and its gradient have a hither...
research
11/21/2021

Semiexplicit Symplectic Integrators for Non-separable Hamiltonian Systems

We construct a symplectic integrator for non-separable Hamiltonian syste...

Please sign up or login with your details

Forgot password? Click here to reset