Fourier Slice Theorem
The Fourier Slice Theorem is the basis of the Filtered Backprojection reconstruction method.
This video is part of the "Computed Tomography and the ASTRA Toolbox" training course, developed at the Vision Lab at the University of Antwerp, Belgium (visielab.uantwerpen.be).
The ASTRA Toolbox is an open source tool for efficient and flexible tomographic reconstruction algorithms. It is being developed at the University of Antwerp, Belgium and at the Centrum Wiskunde & Informatica (CWI), Amsterdam, The Netherlands.
More information on the ASTRA Toolbox can be found at www.astra-toolbox.com
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Пікірлер: 20
Perfect explanation. Three and a half minutes that really brings it to the point
Thanks for making this wonderful video. The Fourier Slice Theorem is astounding! You have provided a nice conceptual guide for me to work out the details for myself. Thanks again!
Thank you very much for this clear explanation it is very much appreciated!!!
Thanks! Very clearly explained. I was only familair with 1D fourier so it seemed a little abstract but now I understand it.
Thank you so much!!! Really easy to understand the basic concept and idea behind it.
Thank you so much!!! You are such a great teacher!!
Thanks, really good explanation :)
Thank you very much for the videos !
Great explanation, thanks!
Clean and nice explanation
very helpful thank you !
The best explanation so far... Thanks so much
Thank you man
Thats really great. But what exactly is f(x,y)? I understand it as an Absorption function at location x and y of the Objekt, related to the density and content of the object
Can you please also explain the FBP algorithm for Photoacoustic Tomography?
Which video discusses Filtered Back Projection?
what does p(theta) mean???
How does this tie in with the Radon Transform?
@thomaswinslow7161
5 жыл бұрын
1D FT of radon transform for angle theta = line at angle theta through the 2D FT for the entire object
Good vid, but I’ll say that it would improve your videos if you could remove the reverb. Clear crisp audio is most pleasant to listen to technical stuff with