dixon

Collection of Dixon fat/water separation methods.

Implementations of methods described in Berstein (see function docstrings for references).

mr_utils.recon.ssfp.dixon.dixon_2pt(IP, OP)[source]

Naive two-point Dixon method of fat/water separation.

Parameters:
  • IP (array_like) – In-phase image (corresponding to 0).
  • OP (array_like) – Out-of-phase image (corresponding to pi).
Returns:

  • W (array_like) – water image
  • F (array_like) – fat image

Notes

“[This implementation] ignores additional image weighting from T2* relaxation, diffusion, and flow and from other phase shifts that could arise from hardware group delays, eddy currents, and B1 receive-field nonuniformity. We have also ignored the water-fat chemical shift separation in both the slice and readout directions” [1].

Implements method described in [1]. Also equations [17.52] in [2].

References

[1](1, 2) Dixon, W. T. (1984). Simple proton spectroscopic imaging. Radiology,
[2]Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.
mr_utils.recon.ssfp.dixon.dixon_2pt_mag(IP, OP)[source]

Solution to two-point Dixon method using magnitude of images.

Parameters:
  • IP (array_like) – In-phase image (corresponding to 0).
  • OP (array_like) – Out-of-phase image (corresponding to pi).
Returns:

  • abs(W) (array_like) – water image
  • abs(F) (array_like) – fat image

Notes

Implements equations [17.53-54] in [4].

References

[4]Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.
mr_utils.recon.ssfp.dixon.dixon_3pt(IP, OP1, OP2, use_2pi=True, method='glover')[source]

Three point Dixon method of fat/water separation.

Parameters:
  • IP (array_like) – In-phase image (corresponding to 0).
  • OP1 (array_like) – Out-of-phase image (corresponding to pi).
  • OP2 (array_like) – Out-of-phase image (corresponding to -pi or 2*pi).
  • use_2pi (bool, optional) – Use 2*pi for OP2 instead of -pi.
  • method ({'vanilla', 'glover', 'chen'}, optional) – Method to use to determine pc, see dixon_pc().
Returns:

  • W (array_like) – water image
  • F (array_like) – fat image
  • B0 (array_like) – B0 inhomogeneity image.

Notes

“The phase difference between the two opposed-phase images is due to B0 inhomogeneity, and they are used to compute phi. The phi map is used to remove the B0 inhomogeneity phase shift from one of the opposed-phase images and thereby determine the dominant species for each pixel (i.e., whether W > F, or vice versa).”

Implements method described [6]. Also implements equations [17.71] in [7].

References

[6]Glover, G. H., & Schneider, E. (1991). Three‐point Dixon technique for true water/fat decomposition with B0 inhomogeneity correction. Magnetic resonance in medicine, 18(2), 371-383.
[7]Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.
mr_utils.recon.ssfp.dixon.dixon_3pt_dpe(I0, I1, I2, theta)[source]

Three point Dixon using direct phase encoding (DPE).

Parameters:
  • I0 (array_like) – In-phase image (corresponding to phi_0 phase).
  • I1 (array_like) – Out-of-phase image (corresponding to phi_0 + phi).
  • I2 (array_like) – Out-of-phase image (corresponding to phi_0 + 2*phi).
  • theta (float) – Phase term.
Returns:

  • W (array_like) – Water image
  • F (array_like) – Fat image.

Notes

Note that theta_0 + theta should not be a multiple of pi!

Implements equations [17.83-84] from [9].

References

[9]Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.
mr_utils.recon.ssfp.dixon.dixon_3pt_eam(I0, I1, I2, method='glover')[source]

Three point Dixon including echo amplitude modulation (EAM).

Parameters:
  • I0 (array_like) – In-phase image (corresponding to phi_0 phase).
  • I1 (array_like) – Out-of-phase image (corresponding to phi_0 + phi).
  • I2 (array_like) – Out-of-phase image (corresponding to phi_0 + 2*phi).
  • method ({'vanilla', 'glover', 'chen'}, optional) – Method to use to determine pc, see dixon_pc().
Returns:

  • W (array_like) – water image
  • F (array_like) – fat image
  • A (array_like) – The susceptibility dephasing map.

Notes

“…under our assumptions, ignoring amplitude effects simply results in a multiplicative error in both water and fat components. This error is usually not serious and can be ignored…there is a SNR penalty for the amplitude correction, and it is best avoided unless there is a specific need to compute A for the application of interest” [8].

Implements equations [17.78] from [8].

References

[8](1, 2) Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.
mr_utils.recon.ssfp.dixon.dixon_extended_2pt(IP, OP, method='glover')[source]

Extended two-point Dixon method for fat/water separation.

Parameters:
  • IP (array_like) – In-phase image (corresponding to 0).
  • OP (array_like) – Out-of-phase image (corresponding to pi).
  • method ({'vanilla', 'glover', 'chen'}, optional) – Method to use to determine pc, see dixon_pc().
Returns:

  • abs(W) (array_like) – water image
  • abs(F) (array_like) – fat image

Notes

Extended 2PD attempts to address the B0 homogeneity problem by using a generalized pc.

Implements equations [17.63] in [5].

References

[5]Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.
mr_utils.recon.ssfp.dixon.dixon_pc(IP, OP, method='vanilla')[source]

Methods to determine pc, fat/water fraction within a voxel.

Parameters:
  • IP (array_like) – In-phase image (corresponding to 0).
  • OP (array_like) – Out-of-phase image (corresponding to pi).
  • method ({'vanilla', 'glover', 'chen'}, optional) – Method to determine pc. See notes.
Returns:

pc – Fat/water fraction.
Return type:

array_like
Raises:

NotImplementedError – When incorrect value for method used.

Notes

method: - ‘vanilla’: sign of W - F. - ‘glover’: maintain continuous image appearance by using cont. p value. - ‘chen’: alternative that performs ‘glover’ and then discretizes.

‘glover’ is implementation of eq [17.62], ‘chen’ is implementation of eq [17.64-65], ‘vanilla’ is eq [17.54] from [3].

References

[3]Notes from Bernstein, M. A., King, K. F., & Zhou, X. J. (2004). Handbook of MRI pulse sequences. Elsevier.