Reconstruction of tomographic images using analog projections and the digital Radon transform

Abstract The digital Radon transform (DRT) can be adapted to reconstruct images from analog projection data. This new technique is a variation of the conventional back-projection method. It requires no pre-filtering of the projection data, straightforward 1D linear interpolation and some simple sorting of projection samples. The DRT enables the use of a form of block-data copy for the reconstruction, which is fast in comparison to the usual methods of back-projection. To obtain reconstructed images of high quality, further intrinsic interpolation is required; the reconstructed image size has to be several times larger than the number of projection samples. We describe an algorithm to convert analog projection data into a form suitable to apply the DRT. We compare the performance of the “standard” DRT and a hybrid version of the DRT to some conventional reconstruction algorithms.

[1]  Jan P. Allebach,et al.  Analysis of error in reconstruction of two-dimensional signals from irregularly spaced samples , 1987, IEEE Trans. Acoust. Speech Signal Process..

[2]  Abderrezak Guessoum,et al.  Fast algorithms for the multidimensional discrete Fourier transform , 1986, IEEE Trans. Acoust. Speech Signal Process..

[3]  Pablo M. Salzberg,et al.  Tomography on the 3D-Torus and Crystals , 1999 .

[4]  Jorge L. C. Sanz,et al.  Computing projections of digital images in image processing pipeline architectures , 1987, IEEE Trans. Acoust. Speech Signal Process..

[5]  Jc Shepherdson,et al.  Machine Intelligence 15 , 1998 .

[6]  Jan Flusser,et al.  Image Representation Via a Finite Radon Transform , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Alfred M. Bruckstein,et al.  The number of digital straight lines on an N×N grid , 1990, IEEE Trans. Inf. Theory.

[8]  Gregory Beylkin,et al.  Discrete radon transform , 1987, IEEE Trans. Acoust. Speech Signal Process..

[9]  G. Herman,et al.  Image reconstruction from linograms: implementation and evaluation. , 1988, IEEE transactions on medical imaging.

[10]  G. Herman,et al.  Discrete tomography : foundations, algorithms, and applications , 1999 .