Principles of Computerized Tomographic Imaging

Kak, Avinash C.; Slaney, Malcolm; Wang, Ge

doi:10.1137/1.9780898719277

Cited by 3,414 publications

(2,738 citation statements)

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“…The reconstruction of the plasma-density profile was done by a process of back-projection 8 and deconvolution. To implement the back-projection, the phase image was first re-sampled onto the projection coordinates, (p,θ), yielding a 'sinogram' (Fig.…”

Section: Resultsmentioning

confidence: 99%

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Single-shot ultrafast tomographic imaging by spectral multiplexing

2012

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Computed tomography has profoundly impacted science, medicine and technology by using projection measurements scanned over multiple angles to permit cross-sectional imaging of an object. The application of computed tomography to moving or dynamically varying objects, however, has been limited by the temporal resolution of the technique, which is set by the time required to complete the scan. For objects that vary on ultrafast timescales, traditional scanning methods are not an option. Here we present a non-scanning method capable of resolving structure on femtosecond timescales by using spectral multiplexing of a single laser beam to perform tomographic imaging over a continuous range of angles simultaneously. We use this technique to demonstrate the first single-shot ultrafast computed tomography reconstructions and obtain previously inaccessible structure and position information for laser-induced plasma filaments. This development enables real-time tomographic imaging for ultrafast science, and offers a potential solution to the challenging problem of imaging through scattering surfaces.

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Section: Resultsmentioning

confidence: 99%

“…5,6 Recently, Li et al 7 have made progress in this direction by demonstrating simultaneous acquisition of four projections using separate singleshot probe lines. Sparse angle-sampling, however, is well known to result in artifacts that can strongly affect the reconstructed images 8 .…”

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confidence: 99%

Single-shot ultrafast tomographic imaging by spectral multiplexing

2012

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“…electrons per detector pixel) and t hm are the lengths of the beam path by which sample voxel of index m is transversed [13]. The probability of observing intensities D h is given by a Poisson distribution [12].…”

Section: Likelihood Function For Absorption Tomographymentioning

confidence: 99%

Autonomous reconstruction and segmentation of tomographic data

Wollgarten

Habeck

2014

Micron

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A Bayesian approach to reconstruction and segmentation of tomographic data is outlined and further detailed for the case of absorption tomography. The algorithm allows the quantification of reconstruction errors and segmentation confidence. Calculation results for various experimental settings (number of projections, incident dose, different materials) are shown and discussed.We are pleased to dedicate this paper to the memory of David J. H. Cockayne. HighlightsSimultaneous tomographic reconstruction and segmentation algorithm Fully self-contained Probabilistic error metrics for both reconstructed densities and segmentation on a voxel basis Highlights (for review)Autonomous reconstruction and segmentation of tomographic data We are pleased to dedicate this paper to the memory of David J. H. Cockayne.

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“…Now a distribution map of µ s can be obtained with a mathematically correct reconstruction procedure because its line integrals collected across 360º are known (Kak and Slaney 2001).…”

Section: Attenuation Correctionmentioning

confidence: 99%