MRI_FFT.ThreeD module

For use when a 3D output array is required.

It includes two classes:

• “Direct3d”, for when all of the k-space data is available immediately, and

• “TwoDDecomp”, or two-dimensional decomposition, for when two dimensional k-space data can be processed during the scan.

class MRI_FFT.ThreeD.Direct3d(shape)

Bases: object

Calculates the inverse Fourier’s transform of a 3D numpy array directly

This class should be used when all of the data is available immediately.

Parameters:shape (1D array) – The shape of the 3D array that contains the k-space data to be transformed

Note

Memory errors can occur with large array sizes.

ifft3D(array3D)

Calculates the 3D inverse Fourier’s Transform of array3D

Parameters:array3D (A complex or real 3D numpy array) – An array of k-space data Returns:The transformed array Return type:A complex64 3D numpy array

class MRI_FFT.ThreeD.TwoDDecomp(shape, inputAxis)

Bases: object

Calculates the inverse Fourier’s transform of a 3D numpy array using 2D decomposition

This class should be used when 2D data becomes available during the 3D scan.

Parameters:

• shape (2D array) – The shape of the 3D array that contains the k-space data to be transformed
• inputAxis (Integer: 0, 1, or 2) – The direction in which to append the 2D arrays. For example, for inputAxis == 0, the arrays will be entered as follows [0, :, :], [1, :, :], etc

Note

Memory errors can occur with large array sizes.

append2D(array2D)

Calculates the 2D iFFT, then appends it to the 3D array.

When the last 2D array is entered, the 3D iFFT is calculated and returned.

Parameters:array2D (A complex or real 2D numpy array) – An array of k-space data Returns:The transformed complete array Return type:A complex64 3D numpy array

Note

2D arrays must be entered in order