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Fourier rebinning algorithm for inverse geometry CT
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Image of FIG. 1.
FIG. 1.

Inverse geometry CT.

Image of FIG. 2.
FIG. 2.

(a) Transverse view and (b) longitudinal view of a PET system. A LOR is characterized by four parameters. and are in-plane parameters, and are longitudinal parameters.

Image of FIG. 3.
FIG. 3.

Reconstructions of the slice at windowed to around 0. (a) FDK and (b) FORE reconstructions of the torso phantom. (c) FDK and (d) FORE reconstructions of the truncated torso phantom. The boxes in (a) depict the regions where noise was estimated.

Image of FIG. 4.
FIG. 4.

(a) FDK and (b) FORE reconstructions of the Shepp–Logan phantom.

Image of FIG. 5.
FIG. 5.

Profile plots along the central vertical axis of the Shepp–Logan reconstructions.

Image of FIG. 6.
FIG. 6.

Theoretical and simulated resolution from the FDK and FORE algorithms. (a) In-plane MTF at and (b) away from the axis. (c) Fourier transform along the axis of the point spread function at 10 and (d) away from the axis.

Image of FIG. 7.
FIG. 7.

Standard deviation from two regions across the volume. (a) Near the axis-of-rotation. (b) away from the axis.

Image of FIG. 8.
FIG. 8.

FDK (top) and FORE (bottom) reconstructions of the numerical Defrise phantom. In this case the vertical direction is the longitudinal direction.

Image of FIG. 9.
FIG. 9.

(a) A 2D FBP reconstruction of the central slice of the anthropomorphic torso phantom using rays from the central source row and detector row only. (b) FDK and (c) FORE reconstructions.


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Numerical torso phantom simulation parameters.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Fourier rebinning algorithm for inverse geometry CT