CT image reconstruction using hexagonal grids

Knaup, Michael; Steckmann, Sven; Bockenbach, Olivier; Kachelrieß, Marc

doi:10.1109/nssmic.2007.4436779

Cited by 16 publications

(9 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was also shown that 12 symmetry axes can be found using hexagonal grids. 36,37 Another approach could lie in the computation of the zeroth projection using rugged and fast methods in Cartesian coordinates, followed by a polar conversion of the system matrix prior to reconstruction. This was not investigated further here, as we believed that the conversion errors would excessively propagate during the iterations.…”

Section: Discussionmentioning

confidence: 99%

Fully 3D iterative CT reconstruction using polar coordinates

2013

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Fully 3D iterative CT reconstruction using polar coordinates

2013

View full text Add to dashboard Cite

show abstract

“…Hexagonal lattices offer consistent connectivity and superior angular resolution motivating their study for several applications such as edge detection, morphological processing, etc., [10], [11]. The utility of this lattice in reconstruction has not been reported in literature barring a method for CT reconstruction which reports improved efficiency and memory management with hexagonal lattice [12]. Since optical cameras acquire images sampled on a square grid, resampling is required to consider the hexagonal grid-based solutions, thus limiting their practical application.…”

Section: Introductionmentioning

confidence: 99%

PET image reconstruction and denoising on hexagonal lattices

Abbas

Sivaswamy

2015

2015 IEEE International Conference on Image Processing (ICIP)

View full text Add to dashboard Cite

Nuclear imaging modalities like Positron emission tomography (PET) are characterized by a low SNR value due to the underlying signal generation mechanism. Given the significant role images play in current-day diagnostics, obtaining noise-free PET images is of great interest. With its higher packing density and larger and symmetrical neighbourhood, the hexagonal lattice offers a natural robustness to degradation in signal. Based on this observation, we propose an alternate solution to denoising, namely by changing the sampling lattice. We use filtered back projection for reconstruction, followed by a sparse dictionary based denoising and compare noise-free reconstruction on the Square and Hexagonal lattices. Experiments with PET phantoms (NEMA, Hoffman) and the Shepp-Logan phantom show that the improvement in denoising, post reconstruction, is not only at the qualitative but also quantitative level. The improvement in PSNR in the hexagonal lattice is on an average between 2 to 10 dB. These results establish the potential of the hexagonal lattice for reconstruction from noisy data, in general.

show abstract

“…These factors have been exploited for image reconstruction. Reconstruction algorithms implemented using hexagonal lattice have been shown to yield images with enhanced quality [11] and to incur reduced computational cost [12], since hexagonal lattice requires 13 percent less samples than square lattice to represent an image. More recently, Faille and Petrou [14] have used hexagonal grid to reconstruct image from very sparse set of non-uniform samples via linear splinebased interpolation.…”

Section: Introductionmentioning

confidence: 99%

A novel approach to generate up-sampled tomographic images using combination of rotated hexagonal lattices

Dixit

Sivaswamy

2010

2010 National Conference on Communications (NCC)

View full text Add to dashboard Cite

Abstract-Generation of upsampled tomographic images via combination of rotated lattices has been explored in [1]. In this paper, we evaluate the existing method using real phantom data. Up-sampled tomographic images are generated via combination of rotated hexagonal lattices. Sinogram data is filtered and back-projected on two hexagonal lattices which are rotated versions of each other. Samples from these lattices are interpolated to generate an up-sampled image defined on a square lattice. These results are compared with direct up-sampling method and image ISR-2 algorithm described in [10]. Two PET phantoms -N EM A and Hof f man brain phantom are used for purpose of evaluation. The results of the proposed method show considerable improvement over direct up-sampled image in terms of contrast, sharpness and imaging artifact; but when compared with ISR-2 generated image, the difference in image quality is not significant. A key advantage of the proposed method is that only two images are required for generating a high resolution image whereas ISR-2 requires k low resolution images for an up-sampling factor of k.

show abstract

CT image reconstruction using hexagonal grids

Cited by 16 publications

References 2 publications

Fully 3D iterative CT reconstruction using polar coordinates

Fully 3D iterative CT reconstruction using polar coordinates

PET image reconstruction and denoising on hexagonal lattices

A novel approach to generate up-sampled tomographic images using combination of rotated hexagonal lattices

Contact Info

Product

Resources

About