Microengineering section, EPFL
Parallel MRI (pMRI) increases the speed of the MRI acquisition by simultaneously receiving
the data through a number of receiver coils with different spatial sensitivities.
These sensitivity maps are used to reconstruct the MR image from missing k-space samples.
Unfortunately, they are patient dependent and have to be calibrated for each person.
The goal of this project is to perform joint reconstruction of the MR image from reduced
k-space sampling and the coil sensitivity maps in order to reduce the acquisition time.
This report outlines the physical principles that underlie the acquisition of MRI data and explains the mathematical model of a reconstruction. By first assuming that the sensitivity maps are known during the iterative reconstruction scheme, we compare two different regularizers; namely, the total variation, and a regularizer based on the Schatten norm of the hessian. We finally show a way to perform the joint reconstruction of the MR image and the sensitivity maps.