Radon

class deepinv.physics.functional.Radon(in_size=None, theta=None, circle=False, parallel_computation=True, fan_beam=False, fan_parameters=None, dtype=torch.float, device=torch.device('cpu'))

Bases: Module

Sparse Radon transform operator.

Parameters:

• in_size (int) – the size of the input image. If None, the size is inferred from the input image.

• theta (torch.Tensor) – the angles at which the Radon transform is computed. Default is torch.arange(180).

• circle (bool) – if True, the input image is assumed to be a circle. Default is False.

• parallel_computation (bool) – if True, all projections are performed in parallel. Requires more memory but is faster on GPUs.

• fan_beam (bool) – If True, use fan beam geometry, if False use parallel beam

• fan_parameters (dict) –

  Only used if fan_beam is True. Contains the parameters defining the scanning geometry. The dict should contain the keys:

  • ”pixel_spacing” defining the distance between two pixels in the image, default: 0.5 / (in_size)

  • ”source_radius” distance between the x-ray source and the rotation axis (middle of the image), default: 57.5

  • ”detector_radius” distance between the x-ray detector and the rotation axis (middle of the image), default: 57.5

  • ”n_detector_pixels” number of pixels of the detector, default: 258

  • ”detector_spacing” distance between two pixels on the detector, default: 0.077

  The default values are adapted from the geometry in https://doi.org/10.5281/zenodo.8307932, where pixel spacing, source and detector radius and detector spacing are given in cm. Note that a to small value of n_detector_pixels*detector_spacing can lead to severe circular artifacts in any reconstruction.

• dtype (torch.dtype) – the data type of the output. Default is torch.float.

• device (str, torch.device) – the device of the output. Default is torch.device(‘cpu’).

forward(x)

Parameters:

x (torch.Tensor) – the input image.