Getting Started

In order to get started we will first gather some MPI data. To this end we enter the Pkg mode in Julia (]) and execute the unit tests of MPIReco

test MPIReco

Now there will be several MPI files in the test directory. All the following examples assume that you entered the test directory and loaded MPIReco using

using MPIReco
cd(joinpath(dirname(pathof(MPIReco)),"..","test"))

First Reconstruction

We will start looking at a very basic reconstruction script

using MPIReco

fSF = MPIFile("SF_MP")
f = MPIFile("dataMP01")

c = reconstruction(fSF, f;
                   SNRThresh=5,
                   frames=1:10,
                   minFreq=80e3,
                   recChannels=1:2,
                   iterations=1,
                   spectralLeakageCorrection=true)

Lets go through that script step by step. First, we create handles for the system matrix and the measurement data. Both are of the type MPIFile which is an abstract type that can for instance be an MDFFile or a BrukerFile.

Using the handles to the MPI datasets we can call the reconstruction function that has various variants depending on the types that are passed to it. Here, we exploit the multiple dispatch mechanism of julia. In addition to the file handles we also apply several reconstruction parameters using keyword arguments. In this case, we set the SNR threshold to 5 implying that only matrix rows with an SNR above 5 are used during reconstruction. The parameter frame decides which frame of the measured data should be reconstructed.

The object c is of type ImageMeta and contains not only the reconstructed data but also several metadata such as the reconstruction parameters being used. More details on the return type are discussed in the Reconstruction Results

Data Storage

One can store the reconstruction result into an MDF file by calling

saveRecoData("filename.mdf", c)

In order to load the data one calls

c = loaddata("filename.mdf", c)

We will next take a closer look at different forms of the reconstruction routine.