A Novel Dictionary-Based Image Reconstruction for Photoacoustic Computed Tomography

A practical solution to improve the field of view in circular scanning-based photoacoustic tomography

One of the primary challenges in ring single-element photoacoustic tomography systems is the low image quality in areas away from the center of the ring. This is mainly due to the limited field of view (FOV) of each transducer, which in turn reduces the imaging FOV. To address this shortcoming, we have put forward a practical and straightforward solution to enhance the FOV of circular scanning-based photoacoustic tomography (CS-PAT). This is accomplished by placing transducers at different angles instead of using a single transducer placed at a normal angle to the imaging target. We also modified the ring scanner inner wall surface to significantly reduce photoacoustic reverberation. By imaging several phantoms, we show a significant improvement in the images generated by our system imaging from 4.1 to over 7 for the signal-to-noise ratio and structural similarity index increased from 41% to 70%.

Miniaturized preamplifier integration in ultrasound transducer design for enhanced photoacoustic imaging

Photoacoustic imaging (PAI) utilizes the photoacoustic effect to record both vascular and functional characteristics of a biological tissue. Photoacoustic signals have typically low amplitude that cannot be read efficiently by data acquisition systems. This necessitates the use of one or more amplifiers. These amplifiers are somewhat bulky (e.g., the ZFL-500LN+, Mini-Circuits, USA, or 351A-3-50-NI, Analog Modules Inc., USA). Here, we describe the fabrication and development process of a transducer with a built-in low-noise preamplifier that is encased within the transducer housing. This new, to the best of our knowledge, design could be advantageous for applications where a compact transducer + preamplifier is required. We demonstrate the performance of this compact detection unit in a laser scanning photoacoustic microscopy system by imaging a rat ear ex vivo and a rat brain vasculature in vivo.

Evaluation of 10 current image reconstruction algorithms for linear array photoacoustic imaging

Various reconstruction algorithms have been implemented for linear array photoacoustic imaging systems with the goal of accurately reconstructing the strength absorbers within the tissue being imaged. Since the existing algorithms have been introduced by different research groups and the context of performance evaluation was not consistent, it is difficult to make a fair comparison between them. In this study, we systematically compared the performance of 10 published image reconstruction algorithms (DAS, UBP, pDAS, DMAS, MV, EIGMV, SLSC, GSC, TR, and FD) using in-vitro phantom data. Evaluations were conducted based on lateral resolution of the reconstructed images, computational time, target detectability, and noise sensitivity. We anticipate the outcome of this study will assist researchers in selecting appropriate algorithms for their linear array PA imaging applications.

Photoacoustic image reconstruction with an objective function using TGV and ESTGV as a regularization functional

Photoacoustic tomographic imaging is a non-invasive medical diagnostic technology for visualizing biological tissue. However, the inverse problem and noise in photoacoustic signals often cause blurred images. Existing regularization methods struggle with staircasing artifacts and edge preservation. To overcome this, an objective function incorporating total generalized variation (TGV) is proposed. However, it failed with high-density Gaussian noise. To address this, an extended version called edge-guided second-order TGV (ESTGV) is introduced. For sparsification, wavelet transform and discrete cosine transform are introduced, while the fast-composite-splitting algorithm is employed for the inverse problem solution. Experimental validation demonstrates the potential of these approaches.

S-Wave Accelerates Optimization-based Photoacoustic Image Reconstruction in vivo

OBJECTIVE

Photoacoustic imaging has undergone rapid development in recent years. To simulate photoacoustic imaging on a computer, the most popular MATLAB toolbox currently used for the forward projection process is k-Wave. However, k-Wave suffers from significant computation time. Here we propose a straightforward simulation approach based on superposed Wave (s-Wave) to accelerate photoacoustic simulation.

METHODS

In this study, we consider the initial pressure distribution as a collection of individual pixels. By obtaining standard sensor data from a single pixel beforehand, we can easily manipulate the phase and amplitude of the sensor data for specific pixels using loop and multiplication operators. The effectiveness of this approach is validated through an optimization-based reconstruction algorithm.

RESULTS

The results reveal significantly reduced computation time compared with k-Wave. Particularly in a sparse 3-D configuration, s-Wave exhibits a speed improvement >2000 times compared with k-Wave. In terms of optimization-based image reconstruction, in vivo imaging results reveal that using the s-Wave method yields images highly similar to those obtained using k-Wave, while reducing the reconstruction time by approximately 50 times.

CONCLUSION

Proposed here is an accelerated optimization-based algorithm for photoacoustic image reconstruction, using the fast s-Wave forward projection simulation. Our method achieves substantial time savings, particularly in sparse system configurations. Future work will focus on further optimizing the algorithm and expanding its applicability to a broader range of photoacoustic imaging scenarios.

PATLAB: A graphical computational software package for photoacoustic computed tomography research

Photoacoustic tomography (PAT) provides high resolution optical images of tissue at depths of up to several centimetres. This modality has been of interest to researchers for at least 30 years and is still the subject of intensive research. However, PAT researchers lack access to a comprehensive open-source graphical simulation and reconstruction software package. In this article, we introduce PATLAB, an open-source MATLAB-based graphical software package that can perform both PAT simulation and image reconstruction. PATLAB is simple to use yet is capable of complex PAT data processing tasks and offers advanced users a framework to build and test new methods.

A Review of Optical Ultrasound Imaging Modalities for Intravascular Imaging

Recent advances in medical imaging include integrating photoacoustic and optoacoustic techniques with conventional imaging modalities. The developments in the latter have led to the use of optics combined with the conventional ultrasound technique for imaging intravascular tissues and applied to different areas of the human body. Conventional ultrasound is a skin contact-based method used for imaging. It does not expose patients to harmful radiation compared to other techniques such as Computerised Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. On the other hand, optical Ultrasound (OpUS) provides a new way of viewing internal organs of the human body by using skin and an eye-safe laser range. OpUS is mostly used for binary measurements since they do not require to be resolved at a much higher resolution but can be used to check for intravascular imaging. Various signal processing techniques and reconstruction methodologies exist for Photo-Acoustic Imaging, and their applicability in bioimaging is explored in this paper.

Approaching closed spherical, full-view detection for photoacoustic tomography

SIGNIFICANCE

Photoacoustic tomography (PAT) is a widely explored imaging modality and has excellent potential for clinical applications. On the acoustic detection side, limited-view angle and limited-bandwidth are common key issues in PAT systems that result in unwanted artifacts. While analytical and simulation studies of limited-view artifacts are fairly extensive, experimental setups capable of comparing limited-view to an ideal full-view case are lacking.

AIMS

A custom ring-shaped detector array was assembled and mounted to a 6-axis robot, then rotated and translated to achieve up to 3.8π steradian view angle coverage of an imaged object.

APPROACH

Minimization of negativity artifacts and phantom imaging were used to optimize the system, followed by demonstrative imaging of a star contrast phantom, a synthetic breast tumor specimen phantom, and a vascular phantom.

RESULTS

Optimization of the angular/rotation scans found ≈212 effective detectors were needed for high-quality images, while 15-mm steps were used to increase the field of view as required depending on the size of the imaged object. Example phantoms were clearly imaged with all discerning features visible and minimal artifacts.

CONCLUSIONS

A near full-view closed spherical system has been developed, paving the way for future work demonstrating experimentally the significant advantages of using a full-view PAT setup.

Tutorial on Development of 3D Vasculature Digital Phantoms for Evaluation of Photoacoustic Image Reconstruction Algorithms

A synthetic phantom model is typically utilized to evaluate the initial performance of a photoacoustic image reconstruction algorithm. The characteristics of the phantom model (structural, optical, and acoustic) are required to be very similar to those of the biological tissue. Typically, generic two-dimensional shapes are used as imaging targets to calibrate reconstruction algorithms. However, these structures are not representative of complex biological tissue, and therefore the artifacts that exist in reconstructed images of biological tissue vasculature are ignored. Real data from 3D MRI/CT volumes can be extrapolated to create high-quality phantom models; however, these sometimes involve complicated pre-processing and mostly are challenging, due to the inaccessibility of these datasets or the requirement for approval to utilize the data. Therefore, it is necessary to develop a 3D tissue-mimicking phantom model consisting of different compartments with characteristics that can be easily modified. In this tutorial, we present an optimized development process of a generic 3D complex digital vasculature phantom model in Blender. The proposed workflow is such that an accurate and easily editable digital phantom can be developed. Other workflows for creating the same phantom will take much longer to set up and require more time to edit. We have made a few examples of editable 3D phantom models, which are publicly available to test and modify.

Randomized multi-angle illumination for improved linear array photoacoustic computed tomography in brain

One of the key challenges in linear array transducer-based photoacoustic computed tomography is to image structures embedded deep within the biological tissue with limited optical energy. Here, we utilized a manually controlled multi-angle illumination technique to allow the incident photons to interact with the imaging targets for longer periods of time and diffuse further in all directions. We have developed and optimized a compact probe that enables manual changes to the angle of illumination while acquiring photoacoustic signals. The performance has been demonstrated and evaluated by imaging complex blood vessel mimicking phantoms in-vitro and sheep brain samples ex-vivo. For effective image reconstruction from the data acquired by multi-angle illumination method, we have utilized a method based on the extraction of maximum intensity. In both cases, multi-angle illumination has out-performed the conventional fixed angle illumination technique to improve the overall image quality. Specifically, extraction of the imaging targets located at greater axial depths was possible using this multi-angle illumination technique.

Transfontanelle photoacoustic imaging: ultrasound transducer selection analysis

Transfontanelle ultrasound imaging (TFUI) is the conventional approach for diagnosing brain injury in neonates. Despite being the first stage imaging modality, TFUI lacks accuracy in determining the injury at an early stage due to degraded sensitivity and specificity. Therefore, a modality like photoacoustic imaging that combines the advantages of both acoustic and optical imaging can overcome the existing TFUI limitations. Even though a variety of transducers have been used in TFUI, it is essential to identify the transducer specification that is optimal for transfontanelle imaging using the photoacoustic technique. In this study, we evaluated the performance of 6 commercially available ultrasound transducer arrays to identify the optimal characteristics for transfontanelle photoacoustic imaging. We focused on commercially available linear and phased array transducer probes with center frequencies ranging from 2.5MHz to 8.5MHz which covers the entire spectrum of the transducer arrays used for brain imaging. The probes were tested on both in vitro and ex vivo brain tissue, and their performance in terms of transducer resolution, size, penetration depth, sensitivity, signal to noise ratio, signal amplification and reconstructed image quality were evaluated. The analysis of selected transducers in these areas allowed us to determine the optimal transducer for transfontanelle imaging, based on vasculature depth and blood density in tissue using ex vivo sheep brain. The outcome of this evaluation identified the two most suitable ultrasound transducer probes for transfontanelle photoacoustic imaging.

Wavelength and pulse energy optimization for detecting hypoxia in photoacoustic imaging of the neonatal brain: a simulation study

Cerebral hypoxia is a severe injury caused by oxygen deprivation to the brain. Hypoxia in the neonatal period increases the risk for the development of neurological disorders, including hypoxic-ischemic encephalopathy, cerebral palsy, periventricular leukomalacia, and hydrocephalus. It is crucial to recognize hypoxia as soon as possible because early intervention improves outcomes. Photoacoustic imaging, using at least two wavelengths, through a spectroscopic analysis, can measure brain oxygen saturation. Due to the spectral coloring effect arising from the dependency of optical properties of biological tissues to the wavelength of light, choosing the right wavelength-pair for efficient and most accurate oxygen saturation measurement and consequently quantifying hypoxia at a specific depth is critical. Using a realistic neonate head model and Monte Carlo simulations, we found practical wavelength-pairs that quantified regions with hypoxia most accurately at different depths down to 22 mm into the cortex neighboring the lateral ventricle. We also demonstrated, for the first time, that the accuracy of the sO₂ measurement can be increased by adjusting the level of light energy for each wavelength-pair. Considering the growing interest in photoacoustic imaging of the brain, this work will assist in a more accurate use of photoacoustic spectroscopy and help in the clinical translation of this promising imaging modality. Please note that explaining the effect of acoustic aberration of the skull is not in the scope of this study.

Subaperture Processing-Based Adaptive Beamforming for Photoacoustic Imaging

Delay-and-sum (DAS) beamformers, when applied to photoacoustic (PA) image reconstruction, produce strong sidelobes due to the absence of transmit focusing. Consequently, DAS PA images are often severely degraded by strong off-axis clutter. For preclinical in vivo cardiac PA imaging, the presence of these noise artifacts hampers the detectability and interpretation of PA signals from the myocardial wall, crucial for studying blood-dominated cardiac pathological information and to complement functional information derived from ultrasound imaging. In this article, we present PA subaperture processing (PSAP), an adaptive beamforming method, to mitigate these image degrading effects. In PSAP, a pair of DAS reconstructed images is formed by splitting the received channel data into two complementary nonoverlapping subapertures. Then, a weighting matrix is derived by analyzing the correlation between subaperture beamformed images and multiplied with the full-aperture DAS PA image to reduce sidelobes and incoherent clutter. We validated PSAP using numerical simulation studies using point target, diffuse inclusion and microvasculature imaging, and in vivo feasibility studies on five healthy murine models. Qualitative and quantitative analysis demonstrate improvements in PAI image quality with PSAP compared to DAS and coherence factor weighted DAS (DAS _CF ). PSAP demonstrated improved target detectability with a higher generalized contrast-to-noise (gCNR) ratio in vasculature simulations where PSAP produces 19.61% and 19.53% higher gCNRs than DAS and DAS _CF , respectively. Furthermore, PSAP provided higher image contrast quantified using contrast ratio (CR) (e.g., PSAP produces 89.26% and 11.90% higher CR than DAS and DAS _CF in vasculature simulations) and improved clutter suppression.

Single laser-shot super-resolution photoacoustic tomography with fast sparsity-based reconstruction

Recently, ℓ 1 -norm based reconstruction approaches have been used with linear array systems to improve photoacoustic resolution and demonstrate undersampled imaging when there is sufficient sparsity in some domain. However, such approaches have yet to beat the half-wavelength resolution limit. In this paper, the ability to beat the half-wavelength diffraction limit is demonstrated using a 5 MHz ring array photoacoustic tomography system and ℓ 1 -norm based reconstruction approaches. We used the array system to image wire targets at ≈ 2 - 3 cm depth in both intralipid scattering solution and water. The minimum observable separation was estimated as 70 ± 10 μ m , improving on the half-wavelength resolution limit of 145 μ m . This improvement was demonstrated even when using a random projection transform to reduce data by 99 % , enabling substantially faster reconstruction times. This is the first photoacoustic tomography approach capable of beating the half-wavelength resolution limit with a single laser shot.

Spatiotemporal Coherence Weighting for In Vivo Cardiac Photoacoustic Image Beamformation

Photoacoustic (PA) image reconstruction generally utilizes delay-and-sum (DAS) beamforming of received acoustic waves from tissue irradiated with optical illumination. However, nonadaptive DAS reconstructed cardiac PA images exhibit temporally varying noise which causes reduced myocardial PA signal specificity, making image interpretation difficult. Adaptive beamforming algorithms such as minimum variance (MV) with coherence factor (CF) weighting have been previously reported to improve the DAS image quality. In this article, we report on an adaptive beamforming algorithm by extending CF weighting to the temporal domain for preclinical cardiac PA imaging (PAI). The proposed spatiotemporal coherence factor (STCF) considers multiple temporally adjacent image acquisition events during beamforming and cancels out signals with low spatial coherence and temporal coherence, resulting in higher background noise cancellation while preserving the main features of interest (myocardial wall) in the resultant PA images. STCF has been validated using the numerical simulations and in vivo ECG and respiratory-signal-gated cardiac PAI in healthy murine hearts. The numerical simulation results demonstrate that STCF weighting outperforms DAS and MV beamforming with and without CF weighting under different levels of inherent contrast, acoustic attenuation, optical scattering, and signal-to-noise (SNR) of channel data. Performance improvement is attributed to higher sidelobe reduction (at least 5 dB) and SNR improvement (at least 10 dB). Improved myocardial signal specificity and higher signal rejection in the left ventricular chamber and acoustic gel region are observed with STCF in cardiac PAI.

Technical considerations in the Verasonics research ultrasound platform for developing a photoacoustic imaging system

Photoacoustic imaging (PAI) is an emerging functional and molecular imaging technology that has attracted much attention in the past decade. Recently, many researchers have used the vantage system from Verasonics for simultaneous ultrasound (US) and photoacoustic (PA) imaging. This was the motivation to write on the details of US/PA imaging system implementation and characterization using Verasonics platform. We have discussed the experimental considerations for linear array based PAI due to its popularity, simple setup, and high potential for clinical translatability. Specifically, we describe the strategies of US/PA imaging system setup, signal generation, amplification, data processing and study the system performance.

The Influence of Diode Laser Intensity Modulation on Photoacoustic Image Quality for Oral Soft Tissue Imaging

Introduction: Imaging technologies have been developed to assist physicians and dentists in detecting various diseases. Photoacoustic imaging (PAI) is a new technique that shows great applicability to soft tissues. This study aimed to investigate the effect of diode laser intensity modulation on photoacoustic (PA) image quality. Methods: The prototype of the PAI system in this study utilized a non-ionizing 532 nm continuouswave (CW) diode laser illumination. Samples in this study were oral soft tissues of Sprague-Dawley rats fixed in 10% formalin solution. PA images were taken ex vivo by using the PAI system. The laser exposure for oral soft tissue imaging was set in various duty cycles (16%, 24%, 31%, 39%, and 47%). The samples were embedded in paraffin, and PA images were taken from the paraffinembedded tissue blocks in a similar method by using duty cycles of 40%, 45%, 50%, 55%, 60% respectively to reveal the influence of the laser duty cycle on PA image quality. Results: The oral soft tissue is clearly shown as a yellow to red area in PA images, whereas the nonbiological material appears as a blue background. The color of the PA image is determined by the PA intensity. Hence, the PA intensity of oral soft tissue was generally higher than that of the nonbiological material around it. The Kruskal-Wallis test followed by Mann-Whitney post-hoc analysis revealed significant differences (P<0.05) in the quality of PA images produced by using a 16%-47% duty cycle of laser intensity modulation for direct imaging of oral soft tissue fixed in 10% formalin solution. The PA image quality of paraffin-embedded tissue was higher than that of direct oral soft tissue images, but no significant differences in PA image quality were found between the groups. Conclusion: The PAI system built in this study can image oral soft tissue. The sample preparation and the diode laser intensity modulation may influence the PA image quality for oral soft tissue imaging. Nonetheless, the influence of diode laser intensity modulation is not significant for the PA image quality of paraffin-embedded tissue.

Y-Net: Hybrid deep learning image reconstruction for photoacoustic tomography in vivo

Conventional reconstruction algorithms (e.g., delay-and-sum) used in photoacoustic imaging (PAI) provide a fast solution while many artifacts remain, especially for limited-view with ill-posed problem. In this paper, we propose a new convolutional neural network (CNN) framework Y-Net: a CNN architecture to reconstruct the initial PA pressure distribution by optimizing both raw data and beamformed images once. The network combines two encoders with one decoder path, which optimally utilizes more information from raw data and beamformed image. We compared our result with some ablation studies, and the results of the test set show better performance compared with conventional reconstruction algorithms and other deep learning method (U-Net). Both in-vitro and in-vivo experiments are used to validated our method, which still performs better than other existing methods. The proposed Y-Net architecture also has high potential in medical image reconstruction for other imaging modalities beyond PAI.

High-Resolution Ultrasound Imaging Enabled by Random Interference and Joint Image Reconstruction

In ultrasound, wave interference is an undesirable effect that degrades the resolution of the images. We have recently shown that a wavefront of random interference can be used to reconstruct high-resolution ultrasound images. In this study, we further improve the resolution of interference-based ultrasound imaging by proposing a joint image reconstruction scheme. The proposed reconstruction scheme utilizes radio frequency (RF) signals from all elements of the sensor array in a joint optimization problem to directly reconstruct the final high-resolution image. By jointly processing array signals, we significantly improved the resolution of interference-based imaging. We compare the proposed joint reconstruction method with popular beamforming techniques and the previously proposed interference-based compound method. The simulation study suggests that, among the different reconstruction methods, the joint reconstruction method has the lowest mean-squared error (MSE), the best peak signal-to-noise ratio (PSNR), and the best signal-to-noise ratio (SNR). Similarly, the joint reconstruction method has an exceptional structural similarity index (SSIM) of 0.998. Experimental studies showed that the quality of images significantly improved when compared to other image reconstruction methods. Furthermore, we share our simulation codes as an open-source repository in support of reproducible research.

Resolution enhancement for flexible microscopic imaging based on dictionary learning

The idea of combining a flexible fiber bundle with the microscopic imaging system provides the possibility of the cross-scale detection of defects and textures on large-scale complex components. However, the pixelization artifacts caused by the inter-core spacing of the fibers degrade the image quality and make it difficult to identify the micro-features. A high-resolution reconstruction strategy is proposed based on dictionary learning. By training the high- and low-resolution image pairs after image registration, a coupled dictionary is obtained. Then high-quality images are obtained from the trained dictionary. Experimental results demonstrate that the pixelization artifacts can be effectively addressed, and the resolution of the reconstructed images can be promoted by 1.8 times.

Skull acoustic aberration correction in photoacoustic microscopy using a vector space similarity model: a proof-of-concept simulation study

Skull bone represents a highly acoustical impedance mismatch and a dispersive barrier for the propagation of acoustic waves. Skull distorts the amplitude and phase information of the received waves at different frequencies in a transcranial brain imaging. We study a novel algorithm based on vector space similarity model for the compensation of the skull-induced distortions in transcranial photoacoustic microscopy. The results of the algorithm tested on a simplified numerical skull phantom, demonstrate a fully recovered vasculature with the recovery rate of 91.9%.

Improving vascular imaging with co-planar mutually guided photoacoustic and diffuse optical tomography: a simulation study

Diffuse optical tomography (DOT) and photoacoustic tomography (PAT) are functional imaging modalities that provide absorption coefficient maps of the tissue. Spatial resolution of DOT is relatively low due to light scattering characteristics of the tissue. On the other hand, although PAT can resolve regions of different absorptions with a high spatial resolution, measuring the absolute value of optical absorptions using PAT is challenging due to unknown light fluence distribution in the tissue. Development of image guidance techniques using a priori information of imaging target structure has been shown to increase the accuracy of DOT. PAT is one such method that can be used as a complementary modality to serve as a guide for DOT image reconstruction. On the other hand, estimated fluence map provided by DOT can be used to quantitatively correct PAT images. In this study we introduce a mutually-guided imaging system for fast and simultaneous optical and photoacoustic measurements of tissue absorption map, where DOT is guided by the PAT image and vice versa. Using the obtained absorption map of the tissue, we then estimate the tissue scattering map. We conducted this study using a series of simulations on digital phantoms and demonstrated the effectiveness of the proposed method.

Investigation of the Effect of the Skull in Transcranial Photoacoustic Imaging: A Preliminary Ex Vivo Study

Although transcranial photoacoustic imaging (TCPAI) has been used in small animal brain imaging, in animals with thicker skull bones or in humans both light illumination and ultrasound propagation paths are affected. Hence, the PA image is largely degraded and in some cases completely distorted. This study aims to investigate and determine the maximum thickness of the skull through which photoacoustic imaging is feasible in terms of retaining the imaging target structure without incorporating any post processing. We identify the effect of the skull on both the illumination path and acoustic propagation path separately and combined. In the experimental phase, the distorting effect of ex vivo sheep skull bones with thicknesses in the range of 0.7~1.3 mm are explored. We believe that the findings in this study facilitate the clinical translation of TCPAI.

Overview of Ultrasound Detection Technologies for Photoacoustic Imaging

Ultrasound detection is one of the major components of photoacoustic imaging systems. Advancement in ultrasound transducer technology has a significant impact on the translation of photoacoustic imaging to the clinic. Here, we present an overview on various ultrasound transducer technologies including conventional piezoelectric and micromachined transducers, as well as optical ultrasound detection technology. We explain the core components of each technology, their working principle, and describe their manufacturing process. We then quantitatively compare their performance when they are used in the receive mode of a photoacoustic imaging system.

Deep learning improves contrast in low-fluence photoacoustic imaging

Low fluence illumination sources can facilitate clinical transition of photoacoustic imaging because they are rugged, portable, affordable, and safe. However, these sources also decrease image quality due to their low fluence. Here, we propose a denoising method using a multi-level wavelet-convolutional neural network to map low fluence illumination source images to its corresponding high fluence excitation map. Quantitative and qualitative results show a significant potential to remove the background noise and preserve the structures of target. Substantial improvements up to 2.20, 2.25, and 4.3-fold for PSNR, SSIM, and CNR metrics were observed, respectively. We also observed enhanced contrast (up to 1.76-fold) in an in vivo application using our proposed methods. We suggest that this tool can improve the value of such sources in photoacoustic imaging.

Dictionary learning technique enhances signal in LED-based photoacoustic imaging

There has been growing interest in low-cost light sources such as light-emitting diodes (LEDs) as an excitation source in photoacoustic imaging. However, LED-based photoacoustic imaging is limited by low signal due to low energy per pulse-the signal is easily buried in noise leading to low quality images. Here, we describe a signal de-noising approach for LED-based photoacoustic signals based on dictionary learning with an alternating direction method of multipliers. This signal enhancement method is then followed by a simple reconstruction approach delay and sum. This approach leads to sparse representation of the main components of the signal. The main improvements of this approach are a 38% higher contrast ratio and a 43% higher axial resolution versus the averaging method but with only 4% of the frames and consequently 49.5% less computational time. This makes it an appropriate option for real-time LED-based photoacoustic imaging.

Development of a Stationary 3D Photoacoustic Imaging System Using Sparse Single-Element Transducers: Phantom Study

Photoacoustic imaging (PAI) is an emerging label-free and non-invasive modality for imaging biological tissues. PAI has been implemented in different configurations, one of which is photoacoustic computed tomography (PACT) with a potential wide range of applications, including brain and breast imaging. Hemispherical Array PACT (HA-PACT) is a variation of PACT that has solved the limited detection-view problem. Here, we designed an HA-PACT system consisting of 50 single element transducers. For implementation, we initially performed a simulation study, with parameters close to those in practice, to determine the relationship between the number of transducers and the quality of the reconstructed image. We then used the greatest number of transducers possible on the hemisphere and imaged copper wire phantoms coated with a light absorbing material to evaluate the performance of the system. Several practical issues such as light illumination, arrangement of the transducers, and an image reconstruction algorithm have been comprehensively studied.

Review of cost reduction methods in photoacoustic computed tomography

Photoacoustic Computed Tomography (PACT) is a major configuration of photoacoustic imaging, a hybrid noninvasive modality for both functional and molecular imaging. PACT has rapidly gained importance in the field of biomedical imaging due to superior performance as compared to conventional optical imaging counterparts. However, the overall cost of developing a PACT system is one of the challenges towards clinical translation of this novel technique. The cost of a typical commercial PACT system originates from optical source, ultrasound detector, and data acquisition unit. With growing applications of photoacoustic imaging, there is a tremendous demand towards reducing its cost. In this review article, we have discussed various approaches to reduce the overall cost of a PACT system, and provided a cost estimation to build a low-cost PACT system.

Streak artifact suppression in photoacoustic computed tomography using adaptive back projection

For photoacoustic computed tomography (PACT), an insufficient number of ultrasound detectors can cause serious streak-type artifacts. These artifacts get overlaid on top of image features, and thus locally jeopardize image quality and resolution. Here, a reconstruction algorithm, termed Contamination-Tracing Back-Projection (CTBP), is proposed for the mitigation of streak-type artifacts. During reconstruction, CTBP adaptively adjusts the back-projection weight, whose value is determined by the likelihood of contamination, to minimize the negative influences of strong absorbers. An iterative solution of the eikonal equation is implemented to accurately trace the time of flight of different pixels. Numerical, phantom and in vivo experiments demonstrate that CTBP can dramatically suppress streak artifacts in PACT and improve image quality.

Photoacoustic/Ultrasound/Optical Coherence Tomography Evaluation of Melanoma Lesion and Healthy Skin in a Swine Model

The marked increase in the incidence of melanoma coupled with the rapid drop in the survival rate after metastasis has promoted the investigation into improved diagnostic methods for melanoma. High-frequency ultrasound (US), optical coherence tomography (OCT), and photoacoustic imaging (PAI) are three potential modalities that can assist a dermatologist by providing extra information beyond dermoscopic features. In this study, we imaged a swine model with spontaneous melanoma using these modalities and compared the images with images of nearby healthy skin. Histology images were used for validation.

Image improvement in linear-array photoacoustic imaging using high resolution coherence factor weighting technique

Background

In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is delay-and-sum (DAS) due to its simple implementation. However, it results in a low quality image affected by the high level of sidelobes. Coherence factor (CF) can be used to address the sidelobes in the reconstructed images by DAS, but the resolution improvement is not good enough, compared to the high resolution beamformers such as minimum variance (MV). In this paper, it is proposed to use high-resolution-CF (HRCF) weighting technique in which MV is used instead of the existing DAS in the formula of the conventional CF.

Results

The higher performance of HRCF is proved numerically and experimentally. The quantitative results obtained with the simulations show that at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improves the full-width-half-maximum of about 91% and 15% and the signal-to-noise ratio about 40% and 14%, respectively.

Conclusion

Proposed method provides a high resolution along with a low level of sidelobes for PAI.

A Guided Wave Transducer with Sprayed Magnetostrictive Powder Coating for Monitoring of Aluminum Conductor Steel-Reinforced Cables

Aluminum conductor steel-reinforced (ACSR) cables are typically used in overhead transmission lines, requiring stringent non-destructive testing owing to the severe conditions they face. Ultrasonic guided wave inspection provides promising online monitoring of the wire breakage of cables with the advantages of high sensitivity, long-range inspection, and full cross-sectional coverage. It is a very popular method to generate and receive guided waves using magnetostrictive and piezoelectric transducers. However, uniformly coupling the acoustic energy excited by transducers into multi-wire structures is always a challenge in the field application of guided waves. Long-term field application of piezoelectric transducers is limited due to the small coupling surface area, localized excitation, and couplant required. Conventional magnetostrictive transducers for steel strand inspection are based on the magnetostrictive effect of the material itself. Two factors affect the transducing performance of the transducers on ACSR cables. On one hand, there is a non-magnetostrictive effect in aluminum wires. On the other hand, the magnetostriction of the innermost steel wires is too weak to generate guided waves. The bias magnetic field is attenuated by the outer layers of aluminum wires. In this paper, an alternative sprayed magnetostrictive powder coating (SMPC) transducer was developed for guided wave generation and detection in ACSR cables. The Fe₈₃Ga₁₇ alloy powder with large magnetostriction was sprayed uniformly on the surfaces of certain sections of the outermost aluminum wires where the transducer would be installed. Experimental investigations were carried out to generate and receive the most commonly used L(0,1) guided waves for wire breakage detection at frequencies of 50 and 100 kHz. The results demonstrate that the discernable reflected waves of the cable end and an artificial defect of three-wire breakage (5.5% reduction in the cable’s cross-sectional area) were received by the transducer with SMPC, which was impossible for the transducer without SMPC. This method makes long-term and online monitoring of ACSR cables feasible due to the high coupling efficiency and good structural surface adaptability.

Numerical and Experimental Investigation of Guided Wave Propagation in a Multi-Wire Cable

Ultrasonic guided waves (UGWs) have attracted attention in the nondestructive testing and structural health monitoring (SHM) of multi-wire cables. They offer such advantages as a single measurement, wide coverage of the acoustic field, and long-range propagation ability. However, the mechanical coupling of multi-wire structures complicates the propagation behaviors of guided waves and signal interpretation. In this paper, UGW propagation in these waveguides is investigated theoretically, numerically, and experimentally from the perspective of dispersion and wave structure, contact acoustic nonlinearity (CAN), and wave energy transfer. Although the performance of all possible propagating wave modes in a multi-wire cable at different frequencies could be obtained by dispersion analysis, it is ineffective to analyze the frequency behaviors of the wave signals of a certain mode, which could be analyzed using the CAN effect. The CAN phenomenon of two mechanically coupled wires in contact was observed, which was demonstrated by numerical guided wave simulation and experiments. Additionally, the measured guided wave energy of wires located in different layers of an aluminum conductor steel-reinforced cable accords with the theoretical prediction. The model of wave energy distribution in different layers of a cable also could be used to optimize the excitation power of transducers and determine the effective monitoring range of SHM.

A Pseudo-Dynamic Delay Calculation Using Optimal Zone Segmentation for Ultra-Compact Ultrasound Imaging Systems

The implementation of dynamic delay calculations (DDCs) is challenging for ultra-compact ultrasound imaging due to the enormous computation and power consumption requirements. Here, we present an efficient pseudo-DDC method based on optimal zone segmentation (PDC-Optimal), which significantly decreases these requirements relative to an unconstrained DDC method: reductions in flip-flops of 84.35% and in look-up tables of 94.19%, respectively. The reductions lead to an up to 94.53% lower dynamic power consumption and provide image quality comparable to the unconstrained DDC method. The proposed PDC-Optimal method also provides adaptive flexibility between beamforming accuracy and battery life using the delay error allowance, a user-definable parameter. A conventional pseudo-DDC method using uniform zone segmentation (PDC-Conv) presented substantial image degradation in the near imaging field when the same number of zone segments was used. Therefore, the PDC-Optimal method provides an efficient yet flexible DDC solution to improve the experiences for ultra-compact ultrasound imaging system users.

Development of Low-Cost Fast Photoacoustic Computed Tomography: System Characterization and Phantom Study

A low-cost Photoacoustic Computed Tomography (PACT) system consisting of 16 single-element transducers has been developed. Our design proposes a fast rotating mechanism of 360o rotation around the imaging target, generating comparable images to those produced by large-number-element (e.g., 512, 1024, etc.) ring-array PACT systems. The 2D images with a temporal resolution of 1.5 s and a spatial resolution of 240 µm were achieved. The performance of the proposed system was evaluated by imaging complex phantom. The purpose of the proposed development is to provide researchers a low-cost alternative 2D photoacoustic computed tomography system with comparable resolution to the current high performance expensive ring-array PACT systems.

The double-stage delay-multiply-and-sum image reconstruction method improves imaging quality in a LED-based photoacoustic array scanner

Light-emitting diode-based photoacoustic imaging is more compact and affordable than laser-based systems, but it has low power and hence a high number of replicates. Here, we describe double-stage delay-multiply-and-sum (DS-DMAS) to improve image quality collected on a LED-based scanner. DS-DMAS was evaluated experimentally using point targets (in different laterals and depths) as well as a hair and a rabbit eye. This algorithm can compensate for the low SNR of LED-based systems and offer better lateral resolution of about 60%, 25%, higher contrast ratio of about 97%, 34%, and better full-width-half-maximum of about 60%, 25%, versus delay-and-sum) and delay-multiply-and-sum, respectively. More importantly, DS-DMAS offers this using a smaller number of frames (only 2% of all the frames). These results indicate that DS-DMAS might be a valuable tool in the translation of LED-based and other low power PAI systems.

Photoacoustic Signal Enhancement: Towards Utilization of Low Energy Laser Diodes in Real-Time Photoacoustic Imaging

In practice, photoacoustic (PA) waves generated with cost-effective and low-energy laser diodes, are weak and almost buried in noise. Reconstruction of an artifact-free PA image from noisy measurements requires an effective denoising technique. Averaging is widely used to increase the signal-to-noise ratio (SNR) of PA signals; however, it is time consuming and in the case of very low SNR signals, hundreds to thousands of data acquisition epochs are needed. In this study, we explored the feasibility of using an adaptive and time-efficient filtering method to improve the SNR of PA signals. Our results show that the proposed method increases the SNR of PA signals more efficiently and with much fewer acquisitions, compared to common averaging techniques. Consequently, PA imaging is conducted considerably faster.