Configuration file settings

b1map-sim is configured by a .toml file.

Table of contents

1. Title and method
2. Mesh
3. Input
4. Body
5. Output
6. Parameters
   1. Double angle (0)
   2. Actual flip-angle (1)
   3. Bloch–Siegert shift (2)
   4. Transceive phase acquisition (3)
7. Monte Carlo

In .toml files, the symbol # marks the rest of the line as a comment, except when inside a string.

Title and method

title = "Example"
method = 0

• The title will appear in the log of the application.
• The method is selected according to the following table.

Mesh

[mesh]
    size = [128,128,8]
    step = [1e-3,1e-3,4e-3] # [m]

• size is the number of voxels of the input data in each direction.
• step is the size of a voxel in meters.

Input

[input]
    body = "body.toml"
    tx-sensitivity = "phantom.h5:/tx_sens" # [T]
    tx-phase = "phantom.h5:/tx_phase" # [rad]

• body is the address of the .toml file containing the parameters of the body. It can be the configuration file itself or another file (useful if the parameters are shared by more cases).
• tx-sensitivity is the address of the transmit sensitivity (magnitude) in tesla. It must be a dataset in an .h5 file.
• tx-phase is the address in an .h5 file of the transmit phase in radians. It must be a dataset in an .h5 file.

Body

[body]
    materials = "phantom.h5:/materials"
    proton-density = "phantom.h5:/rho"
    longitudinal-relaxation = "phantom.h5:/T1" # [ms]
    transverse-relaxation = "phantom.h5:/T2" # [ms]

• materials is the address of the distribution of materials within the body. It must be a dataset in an .h5 file.
• proton-density is the address of the list of the proton density of each material in the body. It must be a dataset in an .h5 file.
• longitudinal-relaxation is the address of the list of the longitudinal relaxations (T1) expressed in millisecond of each material in the body. It must be a dataset in an .h5 file.
• transverse-relaxation is the address of the list of the transverse relaxations (T2) expressed in millisecond of each material in the body. It must be a dataset in an .h5 file.

Output

[output]
    alpha-estimate = "example.h5:/alpha"
    intermediate-images = "example.h5:/imgs"

• alpha-estimate is the address where the estimated flip-angle expressed in radian (or B1+ magnitude expressed in tesla, in the case of Bloch–Siegert shift) will be written. It must be a dataset in an .h5 file.
• intermediate-images is the root of the address where the intermediate images of the b1-mapping procedure will be written. It must be a dataset in an .h5 file.

Given the above example, the real and imaginary parts of the two intermediate images would be stored in the four datasets:
example.h5:/imgs1/real example.h5:/imgs1/imag
example.h5:/imgs2/real example.h5:/imgs2/imag

Parameters

[parameter]
    alpha-nominal = 1.04 # [rad]
    TR = 3000.0 # [ms]
    TE = 20.0 # [ms]
    spoiling = 1.0

• alpha-nominal is the nominal flip-angle that would be obtained if the transmit sensitivity was homogeneous.
• TR is the repetition time of the pulse sequence.
• TE is the echo time of the pulse sequence.
• spoiling is a coefficient for transverse magnetization spoiling: 1 is ideal spoiling, whereas 0 is no spoiling.

In addition, the following parameters are specific for the adopted B1-mapping method.

Double angle (0)

No additional parameters are needed.

Actual flip-angle (1)

[parameter]
    TRratio = 5.0

• TRratio is the ratio between the TR of the two intermediate images.

Bloch–Siegert shift (2)

[parameter]
    bss-offres = 4.0 # [kHz]
    bss-length = 4.0 # [ms]

• bss-offres is the off-resonance frequency of the Bloch–Siegert pulse expressed in kilohertz.
• bss-length is the length of the Bloch–Siegert pulse expressed in millisecond.

The implemented Bloch–Siegert shift method assumes that the Bloch–Siegert pulse has only the selected off-resonance frequency. It is a good approximation of the common Fermi pulse.

Transceive phase acquisition (3)

No additional parameters are needed.

Monte Carlo

[montecarlo]
    samples = 10
    noise = 0.01

• samples is the number of Monte Carlo samples.
• noise is the inverse of the average SNR of the intermediate images.

This section is optional. If it is present, then a number of noisy output (the Monte Carlo samples) are generated in addition to the noiseless ones. The value of noise must be greater than zero, otherwise this section will be ignored.

Given output.alpha-estimate = "example.h5:/alpha", then the 10 samples are stored in
example.h5:/alpha0 example.h5:/alpha1
example.h5:/alpha2 example.h5:/alpha3
example.h5:/alpha4 example.h5:/alpha5
example.h5:/alpha6 example.h5:/alpha7
example.h5:/alpha8 example.h5:/alpha9