How to conduct FBP with fan beam geometry？ about torch-radon

[matteo-ronchetti]

Which angles are you using?

[liuxxxxxx]

Which angles are you using?

Sorry. It's

angles = np.linspace(0, 2*np.pi, 180)

[matteo-ronchetti]

Can you please share the original image and the FPB reconstruction?

[liuxxxxxx]

Can you please share the original image and the FPB reconstruction?

[liuxxxxxx]

Can you please share the original image and the FPB reconstruction?

Here is the test code:

import torch
import imageio
import numpy as np
from torch_radon import RadonFanbeam

img = imageio.imread('original.png') / 65535.
angles = np.linspace(0, 2*np.pi, 180)
radon = RadonFanbeam(512, angles, 512, 512, det_count=739, det_spacing=1.0, clip_to_circle=False)
img = torch.FloatTensor(img).to(torch.device('cuda')).unsqueeze(0).unsqueeze(0)
p = radon.forward(img)
recon = radon.backprojection(radon.filter_sinogram(p))

imageio.imwrite('recon_fbpfan.png', (recon.cpu().squeeze(0).squeeze(0).numpy()*65535).astype(np.uint16))

[matteo-ronchetti]

I see. With your det_count and spacing the areas of the image "outside of the circle" appear only in a few projections and therefore cannot be reconstructed. To solve this issue you can increase the det_count (or spacing) so that det_count*spacing is large enough (I think that >= 1024 should be enough)

[liuxxxxxx]

I see. With your det_count and spacing the areas of the image "outside of the circle" appear only in a few projections and therefore cannot be reconstructed. To solve this issue you can increase the det_count (or spacing) so that det_count*spacing is large enough (I think that >= 1024 should be enough)

I increase the value of det_count and it worked! Thank you so much!