Variable speed of sound compensation in the linear-array photoacoustic tomography using a multi-stencils fast marching method

Lin, Xin; Sun, Mingjian; Yang, Lijun; Shen, Zhiyuan; Shen, Yi; Feng, Naizhang

doi:10.1016/j.bspc.2018.04.012

Cited by 14 publications

(12 citation statements)

References 26 publications

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“…In such cases, reconstruction methods based on an assumption of a homogenous media are invalid. Although some reconstruction methods for heterogeneous media have been investigated, including ray-based propagation, [5][6][7] time reversal, [8][9][10] and model-based [11][12][13] methods, most of them require a prior knowledge of the sound-of-speed (SOS) distribution which is unknown in practice and difficult to estimate from PAI measurements directly. 13 One way to obtain the SOS distributions is to use adjunct ultrasonic imaging data.…”

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confidence: 99%

Passive ultrasound aided acoustic resolution photoacoustic microscopy imaging for layered heterogeneous media

Jin

Zhang

Liu

et al. 2018

Applied Physics Letters

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Photoacoustic imaging reconstructions usually assume a known speed-of-sound (SOS) distribution; however, in most cases, the SOS distribution is not revealed and is difficult to estimate from photoacoustic signals. In this paper, we propose passive ultrasound aided acoustic resolution photoacoustic microscopy which simultaneously reconstructs SOS distributions and photoacoustic images for layered heterogeneous media. The passive ultrasound is a kind of laser-induced acoustic wave generated by a transducer absorbing the backscattered light. It can be used to measure the layer thicknesses due to its sensitivity to structural information and broad bandwidth and further determine the SOS distributions. After estimating the SOS distributions, a phase shift plus interpolation is employed to reconstruct the photoacoustic image for heterogeneous media. Without introducing additional hardware, this method can be conveniently incorporated into a conventional photoacoustic imaging system. A curved shell immersed in water is adopted as a layered heterogeneous phantom, and the proposed method reconstructs the targets (carbon rods) under this shell. Under the test of a 5 MHz focused transducer (NA 0.25), the maximum reconstruction deviation of 1.2 mm carbon rods is only 0.15 mm.

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mentioning

confidence: 99%

Passive ultrasound aided acoustic resolution photoacoustic microscopy imaging for layered heterogeneous media

Jin

Zhang

Liu

et al. 2018

Applied Physics Letters

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“…As a result, optimal focusing with the imaging transducer was limited to a region, at rather large depth (for the imaging transducer) close to the part of the skull in contact with the calibration transducer, and at lateral positions where the skull was sufficiently flat to enable close contact with the calibration transducer. Prior knowledge on the compressional sound speed or thickness of skull [53], [58], [76], [88], [89] and correction based on CT scans [53]- [55] are also impractical on-site as these parameters vary in person [23], [25], [29], [51], [52], [90], [93] and EMS are not always equipped with CT scanners.…”

Section: A Comparison With Previous Relevant Work 1) Estimating the C...mentioning

confidence: 99%

Refraction-Corrected Transcranial Ultrasound Imaging Through the Human Temporal Window Using a Single Probe

Mozaffarzadeh

Verschuur

Verweij

et al. 2022

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Transcranial ultrasound imaging (TUI) is a diagnostic modality with numerous applications, but unfortunately, it is hindered by phase aberration caused by the skull. In this article, we propose to reconstruct a transcranial B-mode image with a refraction-corrected synthetic aperture imaging (SAI) scheme. First, the compressional sound velocity of the aberrator (i.e., the skull) is estimated using the bidirectional headwave technique. The medium is described with four layers (i.e., lens, water, skull, and water), and a fast marching method calculates the travel times between individual array elements and image pixels. Finally, a delay-and-sum algorithm is used for image reconstruction with coherent compounding. The point spread function (PSF) in a wire phantom image and reconstructed with the conventional technique (using a constant sound speed throughout the medium), and the proposed method was quantified with numerical synthetic data and experiments with a bone-mimicking plate and a human skull, compared with the PSF achieved in a ground truth image of the medium without the aberrator (i.e., the bone plate or skull). A phasedarray transducer (P4-1, ATL/Philips, 2.5 MHz, 96 elements, pitch = 0.295 mm) was used for the experiments. The results with the synthetic signals, the bone-mimicking plate, and the skull indicated that the proposed method reconstructs the scatterers with an average lateral/axial localization error of 0.06/0.14 mm, 0.11/0.13 mm, and 1.0/0.32 mm,

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“…The autofocusing technique of searching for an optimal SoS value can mitigate the SoS aberration, but it is still not ideal [52]. The MSFM method can correct the SoS aberration in a heterogeneous medium, but it is impractical because the prior SoS map is inaccessible [51]. To suppress streak artifacts, a sufficient density of data is required in the beamforming process, but using an imaging system with a high number of channels increases the system complexity and cost.…”

Section: Discussionmentioning

confidence: 99%

“…The conventional beamformer is the Fourier beamformer with a single SoS (i.e., 1540 m/s) [50] but the medium is acoustically heterogeneous. The MSFM method can accurately synthesize the PA signals in a heterogeneous medium because this method estimates the acoustic time of flight (ToF) using the eikonal equation and 6 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < utilizes the ToF as the exact time delay in the beamforming process (Supplementary Method 1) [51]. However, the MSFM is not practical because of its prior requirement of the actual SoS map to solve the Eikonal equation.…”

Section: B In Silico Phantom Study In a Heterogeneous Medium And Comp...mentioning

confidence: 99%

A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging

Jeon

Choi

Park

et al. 2021

IEEE Trans. on Image Process.

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Photoacoustic imaging (PAI) has attracted great attention as a medical imaging method. Typically, photoacoustic (PA) images are reconstructed via beamforming, but many factors still hinder the beamforming techniques in reconstructing optimal images in terms of image resolution, imaging depth, or processing speed. Here, we demonstrate a novel deep learning PAI that uses multiple speed of sound (SoS) inputs. With this novel method, we achieved SoS aberration mitigation, streak artifact removal, and temporal resolution improvement all at once in structural and functional in vivo PA images of healthy human limbs and melanoma patients. The presented method produces high-contrast PA images in vivo with reduced distortion, even in adverse conditions where the medium is heterogeneous and/or the data sampling is sparse. Thus, we believe that this new method can achieve high image quality with fast data acquisition and can contribute to the advance of clinical PAI.

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Variable speed of sound compensation in the linear-array photoacoustic tomography using a multi-stencils fast marching method

Cited by 14 publications

References 26 publications

Passive ultrasound aided acoustic resolution photoacoustic microscopy imaging for layered heterogeneous media

Passive ultrasound aided acoustic resolution photoacoustic microscopy imaging for layered heterogeneous media

Refraction-Corrected Transcranial Ultrasound Imaging Through the Human Temporal Window Using a Single Probe

A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging

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