Optimal sinogram sampling with temporally offset pixels in continuous rotation CT

Martin Sjölin; Mats Persson

doi:10.1117/12.2254329

9 March 2017 Optimal sinogram sampling with temporally offset pixels in continuous rotation CT

Martin Sjölin, Mats Persson

Proceedings Volume 10132, Medical Imaging 2017: Physics of Medical Imaging; 101322I (2017) https://doi.org/10.1117/12.2254329
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Insufficient angular sampling in computed tomography can lead to aliasing artifacts that impair the quality of the reconstructed images. However, the angular sampling rate is often constrained due to practical limitations, such as the bandwidth of the data read-out or read-out noise. In this work, we present a new sampling scheme that allows aliasing-free image reconstruction with fewer angular samples. This is achieved by introducing a temporal offset between the samples acquired by adjacent detector pixels in the detector array. The temporal shift implies that the positions where the detector pixels sample the 2D Radon transform are interleaved in the angular direction, and if the shift is carefully selected, an optimal (hexagonal) sampling grid can be obtained. Optimal sampling grids are particularly effective in tomographic imaging since the bowtie-shaped spectral support of the sinogram allows a close tiling of the replicated spectra. We derive the sampling requirements when the proposed method is used and demonstrate that the obtained sampling grid reduces the aliasing artifacts compared to standard rectangular sampling at equal number of angular samples in simulated and experimental images. It is shown that the required number of angular samples can be reduced by 25-40%. The method is robust and easy to implement, and can therefore be of practical use for CT imaging where the number of views is limited.

Citation Download Citation

Martin Sjölin and Mats Persson "Optimal sinogram sampling with temporally offset pixels in continuous rotation CT", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101322I (9 March 2017); https://doi.org/10.1117/12.2254329

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