PolyOrderMaskGenerator

class deepinv.physics.generator.PolyOrderMaskGenerator(*args, poly_order=8, **kwargs)

Bases: BaseMaskGenerator

Generator for MRI Cartesian acceleration masks using polynomial variable density.

Generates a mask of vertical lines for MRI acceleration with fixed sampling in low frequencies (center of k-space) and polynomial order sampling in the high frequencies.

This is achieved by the following:

1. Create 1D polynomial function \((1 - r)^{p}\) where \(r\) is the distance from the centre and \(p\) is the polynomial order.

2. Scale so that its mean matches desired acceleration factor

3. Use the function as a probability density function (pdf) to sample from a Bernoulli.

The mask is repeated across channels and randomly varies across batch dimension.

Algorithm taken from Millard and Chiew.

Examples:

>>> from deepinv.physics.generator.mri import PolyOrderMaskGenerator
>>> generator = PolyOrderMaskGenerator((2, 128, 128), acceleration=8, center_fraction=0.04, poly_order=8)
>>> params = generator.step(batch_size=1)
>>> mask = params["mask"]
>>> mask.shape
torch.Size([1, 2, 128, 128])

For other parameter descriptions see deepinv.physics.generator.mri.BaseMaskGenerator

Parameters:

poly_order (int) – polynomial order of the sampling pdf