Compressed Sensing for Ultrasound Computed Tomography

Sloun, Rjg Ruud van; Pandharipande, Ashish; Mischi, Massimo; Demi, Libertario

doi:10.1109/tbme.2015.2422135

Cited by 46 publications

(21 citation statements)

References 16 publications

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“…The normalized error and similar performance indexes such as Mean Normalized Absolute Error (MNAE), Root Mean Squared Error (RMSE) are used to evaluate the reconstruction of ultrasound tomography in some relative work [9, 29–32]. In this paper, we add one more performance index (Q-index) to compare our work (DCS-DBIM) with DBIM.…”

Section: Resultsmentioning

confidence: 99%

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Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography

et al. 2017

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BackgroundA well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared to the current gold-standard X-ray mammography. Based on inverse scattering technique, ultrasound tomography uses some material properties such as sound contrast or attenuation to detect small targets. The Distorted Born Iterative Method (DBIM) based on first-order Born approximation is an efficient diffraction tomography approach. One of the challenges for a high quality reconstruction is to obtain many measurements from the number of transmitters and receivers. Given the fact that biomedical images are often sparse, the compressed sensing (CS) technique could be therefore effectively applied to ultrasound tomography by reducing the number of transmitters and receivers, while maintaining a high quality of image reconstruction.MethodsThere are currently several work on CS that dispose randomly distributed locations for the measurement system. However, this random configuration is relatively difficult to implement in practice. Instead of it, we should adopt a methodology that helps determine the locations of measurement devices in a deterministic way. For this, we develop the novel DCS-DBIM algorithm that is highly applicable in practice. Inspired of the exploitation of the deterministic compressed sensing technique (DCS) introduced by the authors few years ago with the image reconstruction process implemented using l 1 regularization.ResultsSimulation results of the proposed approach have demonstrated its high performance, with the normalized error approximately 90% reduced, compared to the conventional approach, this new approach can save half of number of measurements and only uses two iterations. Universal image quality index is also evaluated in order to prove the efficiency of the proposed approach.ConclusionsNumerical simulation results indicate that CS and DCS techniques offer equivalent image reconstruction quality with simpler practical implementation. It would be a very promising approach in practical applications of modern biomedical imaging technology.

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Section: Resultsmentioning

confidence: 99%

“…Random measurement approach in the detection geometry configuration is proposed in [8, 9]. A set of measurements of the scattered field is performed using sets of receiver’s random positions.…”

Section: Introductionmentioning

confidence: 99%

Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography

et al. 2017

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“…Van Sloun et al [55] proposed randomly-apodized monofrequent emissions from a circular array in two-dimensional tomography. These outperformed sparse SA acquisition sequences using only a few emissions from random elements.…”

Section: A Related Workmentioning

confidence: 99%

Notice of Removal: Random incident sound waves for fast compressed pulse-echo ultrasound imaging

Schiffner

Schmitz

2017

2017 IEEE International Ultrasonics Symposium (IUS)

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Established image recovery methods in fast ultrasound imaging, e.g. delay-and-sum, trade the image quality for the high frame rate. Cutting-edge inverse scattering methods based on compressed sensing (CS) disrupt this tradeoff via a priori information. They iteratively recover a high-quality image from only a few sequential pulse-echo measurements or less echo signals, if (i) a known dictionary of structural building blocks represents the image almost sparsely, and (ii) their individual pulse echoes, which are predicted by a linear model, are sufficiently uncorrelated. The exclusive modeling of the incident waves as steered plane waves or cylindrical waves, however, has so far limited the convergence speed, the image quality, and the potential to meet condition (ii).Motivated by the benefits of randomness in CS, a novel method for the fast compressed acquisition and the subsequent recovery of images is proposed to overcome these limitations. It recovers the spatial compressibility fluctuations in weakly-scattering soft tissue structures, where an orthonormal basis meets condition (i), by a sparsity-promoting ℓq-minimization method, q ∈ [0; 1]. A realistic d-dimensional model, d ∈ {2, 3}, accounting for diffraction, single monopole scattering, the combination of powerlaw absorption and dispersion, and the specifications of a planar transducer array, predicts the pulse echoes of the individual basis functions. Three innovative types of incident waves, whose syntheses leverage random apodization weights, time delays, or combinations thereof, aid in meeting condition (ii).In two-dimensional numerical simulations, single realizations of these waves outperform the prevalent quasi-plane wave for both the canonical and the Fourier bases. They significantly decorrelate the pulse echoes, e.g. they reduce the full extents at half maximum of the point spread functions by up to 73.7 %. For a tissue-mimicking phantom and q ∈ {1, 0.5}, they improve the convergence speed and the image quality in terms of the mean structural similarity indices and the relative root meansquared errors by up to {2.7 %, 22.9 %}, {44.1 %, 55.5 %}, and {42 %, 60.5 %}, respectively.Index Terms-random incident waves, inverse scattering, compressed sensing, sparse regularization, ultrafast ultrasound imaging, computational ultrasound imaging, fast multipole method, GPU computing

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“…The ultrasonic computerized tomography technique is used to detect internal defects of non-transparent objects [1,2]. There are many research reports on ultrasonic computerized tomography systems for non-destructive inspection to find hidden defects or quality problems [3].…”

Section: Introductionmentioning

confidence: 99%

Improved image reconstruction based on ultrasonic transmitted wave computerized tomography on concrete

Fan

Zhu

2018

J Image Video Proc.

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Considering the non-uniqueness and instability of concrete defect detection in construction engineering, ultrasonic time of flight data and maximum likelihood expectation maximization algorithm were proposed to improve the readability of the ultrasonic reconstruction image. Ultrasonic transmitted waves reflect internal information when through concrete structures. Measurement signals were regularized and processed as transit time parameters. Maximum likelihood expectation maximization algorithm was optimized for image reconstruction of the concrete structure. The interpolation data as the density of measurement data was used to improve the readability of reconstruction images. The experimental measurement system, improved image reconstruction algorithm, and interpolation method were verified in detail by using simulation and concrete phantoms. The proposed image reconstruction technique based on maximum likelihood expectation maximization overcame the disadvantages of the traditional image reconstruction method, and it was effective to improve the accuracy and the quality of image reconstruction on concrete. Time of flight data and normalized interpolation were discussed in detail during image reconstruction. The results showed that it could make the position of an abnormal object more obvious, and it was more accurate for reflecting the internal structure of concrete.

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Compressed Sensing for Ultrasound Computed Tomography

Cited by 46 publications

References 16 publications

Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography

Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography

Notice of Removal: Random incident sound waves for fast compressed pulse-echo ultrasound imaging

Improved image reconstruction based on ultrasonic transmitted wave computerized tomography on concrete

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