Adaptive dual-speed ultrasound and photoacoustic computed tomography

Zhang, Yachao; Wang, Lidai

doi:10.1016/j.pacs.2022.100380

Cited by 16 publications

(11 citation statements)

References 32 publications

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“…Hence, the Fredholm integral eigenvalue problem in ( 2) is discretized and simplified to the (infinite) matrix eigenvalue problem shown in Equation (14). For numerical simulations, the problem in Equation (14) needs to be truncated to a finite dimension. The terms in Q k,m eventually go to zero for sufficiently large indices.…”

Section: Fourier Series Expansion Methods For Optimal Waveformmentioning

confidence: 99%

“…Photoacoustic imaging systems for biomedical applications combine the advantages of both optical and acoustical imaging methods and have thus been attracting researchers' attention in recent decades [1][2][3][4][5]. Many attempts have been made to improve the Signalto-Noise Ratio (SNR) of a photoacoustic imaging system [6][7][8][9][10][11][12][13][14]. However, in the context of the selection of the transmitted waveform, most recent studies are still based on either chirps or square pulses, and occasionally Gaussian pulses [15,16] or pulse trains similar to pulsed sinusoids with a high-carrier frequency [17].…”

Section: Introductionmentioning

confidence: 99%

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Waveform Selection Based on Discrete Prolate Spheroidal Sequences for Near-Optimal SNRs for Photoacoustic Applications

Sun,

Baddour

2023

Photonics

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Waveform engineering is an important topic in imaging and detection systems. Waveform design for the optimal Signal-to-Noise Ratio (SNR) under energy and duration constraints can be modelled as an eigenproblem of a Fredholm integral equation of the second kind. SNR gains can be achieved using this approach. However, calculating the waveform for optimal SNR requires precise knowledge of the functional form of the absorber, as well as solving a Fredholm integral eigenproblem which can be difficult. In this paper, we address both those difficulties by proposing a Fourier series expansion method to convert the integral eigenproblem to a small matrix eigenproblem which is both easy to compute and gives a heuristic view of the effects of different absorber kernels on the eigenproblem. Another important result of this paper is to provide an alternate waveform, the Discrete Prolate Spheroidal Sequences (DPSS), as the input waveform to obtain near optimal SNR that does not require the exact form of the absorber to be known apriori.

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Section: Fourier Series Expansion Methods For Optimal Waveformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Waveform Selection Based on Discrete Prolate Spheroidal Sequences for Near-Optimal SNRs for Photoacoustic Applications

Sun,

Baddour

2023

Photonics

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“…In the Bayesian setting, errors due to uncertainties in the SoS can be compensated for using Bayesian approximation error modelling [27] , but the method is computationally intensive. More practically, methods have been proposed to estimate the SoS automatically, by maximising an image quality metric or similar [28] , [29] , [30] , [31] , [32] , [33] . However, all of these proposed methods for accounting for SoS heterogeneities in PA reconstruction either require additional hardware, prior knowledge of the target, or cannot be applied in real-time, or are not applicable to the one-sided measurements of interest here.…”

Section: Introductionmentioning

confidence: 99%

Compensating unknown speed of sound in learned fast 3D limited-view photoacoustic tomography

Poimala,

Cox,

Hauptmann

2024

Photoacoustics

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“…Noninvasive imaging of blood vessels can be performed by PAI to provide high-resolution vascular imaging for preoperative planning. Photoacoustic computed tomography (PACT) 29 , 30 is an embodiment of PAI. Compared with ultrasound imaging, PACT has rich internal and external optical contrast, and it has advantages in high-resolution imaging of subcutaneous microvessels 31 , 32 .…”

Section: Introductionmentioning

confidence: 99%

Photoacoustic-enabled automatic vascular navigation: accurate and naked-eye real-time visualization of deep-seated vessels

Pan

Wang

et al. 2023

Adv. Photon. Nexus

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Accurate localization of blood vessels with image navigation is a key element in vascular-related medical research and vascular surgery. However, current vascular navigation techniques cannot provide naked-eye visualization of deep vascular information noninvasively and with high resolution, resulting in inaccurate vascular anatomy and diminished surgical success rates. Here, we introduce a photoacousticenabled automatic vascular navigation method combining photoacoustic computed tomography with augmented and mixed reality, for the first time, to our knowledge, enabling accurate and noninvasive visualization of the deep microvascular network within the tissues in real time on a real surgical surface. This approach achieves precise vascular localization accuracy (<0.89 mm) and tiny vascular relocation latency (<1 s) through a zero-mean normalization idea-based visual tracking algorithm and a curved surfacefitting algorithm. Further, the subcutaneous vessels of minimum diameter (∼0.15 mm) in rabbit thigh and the maximum depth (∼7 mm) in human arm can be vividly projected on the skin surface with a computer visionbased projection tracking system to simulate preoperative and intraoperative vascular localization. Thereby, this strategy provides a way to visualize deep vessels without damage on the surgical surface and with precise image navigation, opening an avenue for the application of photoacoustic imaging in surgical operations.

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Adaptive dual-speed ultrasound and photoacoustic computed tomography

Cited by 16 publications

References 32 publications

Waveform Selection Based on Discrete Prolate Spheroidal Sequences for Near-Optimal SNRs for Photoacoustic Applications

Waveform Selection Based on Discrete Prolate Spheroidal Sequences for Near-Optimal SNRs for Photoacoustic Applications

Compensating unknown speed of sound in learned fast 3D limited-view photoacoustic tomography

Photoacoustic-enabled automatic vascular navigation: accurate and naked-eye real-time visualization of deep-seated vessels

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