Free Induction Decay

First of all, let's use the KomaMRI package and define the default scanner.

using KomaMRI, Suppressor
sys = Scanner(); # default hardware definition

The free induction decay is the simplest observable NMR signal. This signal is the one that follows a single tipping RF pulse. To recreate this experiment, we will need to define a Sequence with 2 blocks.

The first block containing an RF pulse with a flip-angle of 90 deg,

ampRF = 2e-6                        # 2 uT RF amplitude
durRF = π / 2 / (2π * γ * ampRF)    # required duration for a 90 deg RF pulse
exc = RF(ampRF,durRF);

and the second block containing the ADC.

nADC = 8192         # number of acquisition samples
durADC = 250e-3     # duration of the acquisition
delay =  1e-3       # small delay
acq = ADC(nADC, durADC, delay);

Finally, we concatenate the sequence blocks to create the final sequence.

seq = Sequence()  # empty sequence
seq += exc        # adding RF-only block
seq += acq        # adding ADC-only block
p1 = plot_seq(seq; slider=false, height=300)

Now, we will define a Phantom with a single spin at   with    and   .

obj = Phantom(x=[0.], T1=[1000e-3], T2=[100e-3]);

Finally, to simulate we will need to use the function simulate (note how the use of the @suppress macro prevents internal messages from being printed by the function):

raw = @suppress simulate(obj, seq, sys);

To plot the results we will need to use the plot_signal function

p2 = plot_signal(raw; slider=false, height=300)

Nice!, we can see that follows an exponential decay   as expected.

For a little bit of spiciness, let's add off-resonance to our example. We will use    . For this, we will need to add a definition for Δw in our Phantom

obj = Phantom(x=[0.], T1=[1000e-3], T2=[100e-3], Δw=[-2π*100])# and simulate again.

raw = @suppress simulate(obj, seq, sys)
p3 = plot_signal(raw; slider=false, height=300)

The signal now follows an exponential of the form    . The addition of   to the signal will generate a shift in the image space (Fourier shifting property). This effect will be better visualized and explained in later examples.

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