Experimental Realisation of High-sensitivity Laboratory X-ray Grating-based Phase-contrast Computed Tomography

Birnbacher, Lorenz; Willner, Marian; Velroyen, Astrid; Marschner, Mathias; Hipp, Alexander; Meiser, Jan; Koch, Frieder; Schröter, Tobias J.; Kunka, N.; Mohr, Jürgen; Pfeiffer, Franz; Herzen, Julia

doi:10.1038/srep24022

Cited by 67 publications

(59 citation statements)

References 43 publications

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“…The average intensity for the measurements performed with w ¼ 2.0 lm was higher than that for w ¼ 1.0 lm or w ¼ 0.9 lm [(6.72 6 0.14) Â 10 À3 s À1 lm À2 versus (3.26 6 0.14) Â 10 À3 s À1 lm À2 and (2.66 6 0.14) Â 10 À3 s À1 lm À2 , respectively]. Thus, the highest set-up sensitivity 24 is achieved with w ¼ 2.0 lm, which was used for the tomographic scans presented in this communication.…”

Section: Resultsmentioning

confidence: 93%

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Implementation of a double-grating interferometer for phase-contrast computed tomography in a conventional system nanotom® m

et al. 2018

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Visualizing the internal architecture of large soft tissue specimens within the laboratory environment in a label-free manner is challenging, as the conventional absorption-contrast tomography yields a poor contrast. In this communication, we present the integration of an X-ray double-grating interferometer (XDGI) into an advanced, commercially available micro computed tomography system nanotom ® m with a transmission X-ray source and a micrometer-sized focal spot. The performance of the interferometer is demonstrated by comparing the registered three-dimensional images of a human knee joint sample in phase- and conventional absorption-contrast modes. XDGI provides enough contrast (1.094 ± 0.152) to identify the cartilage layer, which is not recognized in the conventional mode (0.287 ± 0.003). Consequently, the two modes are complementary, as the present XDGI set-up only reaches a spatial resolution of (73 ± 6) μ m, whereas the true micrometer resolution in the absorption-contrast mode has been proven. By providing complimentary information, XDGI is especially a supportive quantitative method for imaging soft tissues and visualizing weak X-ray absorbing species in the direct neighborhood of stronger absorbing components at the microscopic level.

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Section: Resultsmentioning

confidence: 93%

“…The three-grating setup, Talbot-Lau interferometer, works with conventional sources. [22][23][24] However, introduction of the source grating to enhance a spatial coherence reduces an available photon flux. Measurements in a Talbot configuration with two gratings are performed with micro-focus tubes 25 and multiline 26 and liquid-metal-jet 27 sources.…”

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confidence: 99%

Implementation of a double-grating interferometer for phase-contrast computed tomography in a conventional system nanotom® m

et al. 2018

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“…For the past two decades, grating‐based x‐ray phase contrast imaging has shown promising applications in medical imaging and material science . In grating‐based phase contrast imaging, the signal, which is the local moiré fringe shift ϕ for a given refraction angle θ , is usually given by

ϕ = ϕ^{o} - ϕ^{b} = S θ .

here,

ϕ^{o}

ϕ^{b}

are the extracted phase signals from the object scan (object present in x‐ray beam) and air scan (object absent from x‐ray beam), respectively.…”

Section: Introductionmentioning

confidence: 99%

“…For the past two decades, grating-based x-ray phase contrast imaging has shown promising applications in medical imaging and material science. [1][2][3][4][5][6][7][8][9][10][11][12] In grating-based phase contrast imaging, the signal, which is the local moir e fringe shift / for a given refraction angle h, is usually given by…”

Section: Introductionmentioning

confidence: 99%

Is high sensitivity always desirable for a grating‐based differential phase contrast imaging system?

Zhang

et al. 2020

Medical Physics

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Purpose In grating‐based x‐ray differential phase contrast (DPC) imaging, the measured signal amplitude of the phase shift induced by an image object is proportional to the so‐called system sensitivity. Therefore, to achieve a better signal‐to‐noise (SNR) for improved imaging performance, it is generally believed that one should increase the system sensitivity by reducing the period of the analyzer grating or increasing the distance between the phase grating and analyzer grating. The purpose of this work is to theoretically and experimentally demonstrate that there is an optimal system sensitivity to attain the highest SNR for a given task provided that the standard phase‐stepping acquisition and phase retrieval methods are used. When system sensitivity goes beyond this optimal value, SNR decreases and the imaging performance deteriorates. Methods Due to the fundamental fact that the measured phase signal is a cyclic variable, the phase wrapping effect is inevitable in DPC imaging when the system sensitivity increases. The phase wrapping effect appears in both signal and noise measurements. The effect in the signal measurement is manifested in the so‐called signal statistical bias and such effect often impacts the accuracy of the measurement. The phase wrapping effect also appears in the noise variance measurement and impacts the precision of the measurement. A thorough theoretical analysis was performed in this work to demonstrate the quantitative impacts of phase wrapping on both signal bias and noise variance and thus on the actual system SNR. The joint effect of phase wrapping in both the signal bias and noise variance yields an optimal system sensitivity to achieve the highest SNR. Both extensive numerical simulation studies and experimental studies were performed to validate the theoretical analysis. Results Both theoretical analysis and experimental studies show that the SNR of the DPC signal is not always proportional to the sensitivity due to the cyclic nature of the signal and the phase wrapping effect. For a given refraction angle and exposure level, there exists an optimal sensitivity factor that maximizes the SNR, beyond which, increasing the sensitivity will decrease the SNR. Conclusions Increase of system sensitivity does not always improve x‐ray DPC imaging performance provided that the standard phase‐stepping acquisition and phase retrieval methods are used.

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“…Recently, grating-based x-ray multicontrast imaging has attracted a lot of interest in the medical imaging field. [1][2][3][4][5][6][7][8][9][10][11][12][13][14] By incorporating three x-ray gratings, a conventional x-ray absorption contrast imaging system can be upgraded into an x-ray multicontrast imaging system, which can generate three sets of images with distinctive and endogenous contrast mechanisms: the conventional absorption contrast, the differential phasecontrast (DPC), and the dark-field contrast. The DPC and dark-field contrast have been found to be complementary to the conventional absorption contrast.…”

Section: Introductionmentioning

confidence: 99%

Studies of signal estimation bias in grating-based x-ray multicontrast imaging

Zhang

et al. 2017

Med. Phys.

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Purpose: In grating-based x-ray multi-contrast imaging, signals of three contrast mechanisms-absorption contrast, differential phase contrast (DPC), and dark-field contrast-can be estimated from the same set of acquired data. The estimated signals, N0 (related to absorption), N1 (related to dark-field), and φ (related to DPC) may be intrinsically biased. However, it is yet unclear how large these biases are and how the data acquisition parameters affect the biases in the extracted signals. The purpose of this paper was to address these questions. Methods: The biases of the extracted signals (i.e., N0, N1 and φ) were theoretically studied for a well-known signal estimation method. Experimental data acquired from a grating-based x-ray multi-contrast benchtop imaging system with a photon counting detector were used to validate the theoretical results for the signal biases of the three contrast mechanisms. Results: Both theoretical and experimental studies showed the following results: (1) The bias of signal estimation for the absorption contrast signal is zero; (2) The bias of signal estimation for N1 is inversely proportional to the number of phase steps and to the average fringe visibility of the grating interferometer, but the ratio between the bias and the signal level (i.e., the relative bias) is independent of the number of phase steps; (3) The bias of signal estimation for φ depends on the mean DPC signal level, the total exposure level of the multi-contrast data acquisition, and the mean fringe visibility of the interferometer. Conclusions: In grating-based x-ray multi-contrast imaging, the estimated absorption contrast signal is unbiased; the estimated dark-field contrast signal is biased, but the relative bias is only dependent on the mean fringe visibility of the interferometer and the exposure level. The estimated DPC signal may be biased, and the bias level depends on the mean signal level, the exposure level, and the interferometer performance.

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Experimental Realisation of High-sensitivity Laboratory X-ray Grating-based Phase-contrast Computed Tomography

Cited by 67 publications

References 43 publications

Implementation of a double-grating interferometer for phase-contrast computed tomography in a conventional system nanotom® m

Implementation of a double-grating interferometer for phase-contrast computed tomography in a conventional system nanotom® m

Is high sensitivity always desirable for a grating‐based differential phase contrast imaging system?

Studies of signal estimation bias in grating-based x-ray multicontrast imaging

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