Photoacoustic Image Reconstruction Research Articles

Frequency-radial duality based photoacoustic image reconstruction

Photoacoustic image reconstruction algorithms are usually slow due to the large sizes of data that are processed. This paper proposes a method for exact photoacoustic reconstruction for the spherical geometry in the limiting case of a continuous aperture and infinite measurement bandwidth that is faster than existing methods namely (1) backprojection method and (2) the Norton-Linzer method [S. J. Norton and M. Linzer, "Ultrasonic reflectivity imaging in three dimensions: Exact inverse scattering solution for plane, cylindrical and spherical apertures," Biomedical Engineering, IEEE Trans. BME 28, 202-220 (1981)]. The initial pressure distribution is expanded using a spherical Fourier Bessel series. The proposed method estimates the Fourier Bessel coefficients and subsequently recovers the pressure distribution. A concept of frequency-radial duality is introduced that separates the information from the different radial basis functions by using frequencies corresponding to the Bessel zeros. This approach provides a means to analyze the information obtained given a measurement bandwidth. Using order analysis and numerical experiments, the proposed method is shown to be faster than both the backprojection and the Norton-Linzer methods. Further, the reconstructed images using the proposed methodology were of similar quality to the Norton-Linzer method and were better than the approximate backprojection method.

PHOTOACOUSTIC SIGNALS DENOISING BASED ON EMPIRICAL MODE DECOMPOSITION AND ENERGY-WINDOW METHOD

In the process of photoacoustic imaging (PAI), the photoacoustic signals are polluted by a strong background white noise, which is caused by many factors such as the system thermal noise or short noise, the tissue reflecting or scattering interference, and the impedance match lack between the transducer and tissue. The inevitable noise can degrade the contrast sensitivity of photoacoustic images seriously. In this paper, based on the energy window, a CMSE-EMD denoising method is employed to photoacoustic image reconstruction. Results of the simulation demonstrate that it can eliminate the image artifacts more effectively and achieve great improvement in image quality.

Photoacoustic computed tomography correcting for heterogeneity and attenuation.

We report an investigation of image reconstruction in photoacoustic tomography for objects that possess heterogeneous material and acoustic attenuation distributions. When the object contains materials, such as bone and soft-tissue, that are modeled using power law attenuation models with distinct exponents, we demonstrate that the effects of acoustic attenuation due to the most strongly attenuating material can be compensated for if the attenuation of the other less attenuating material(s) are neglected. Experiments with phantom objects are presented to validated our findings.

Direction Study of Multi-element Linear Transducer Array Based on Photoacoustic Imaging

In order to approve the direction property of multi-element linear ultrasonic transducer array, the multi-element phase-controlled technique was adopted. Here we have explored the detected direction influence from dominant frequency, number of multi-element transducer and space between transducer on direction of multi-element linearultrasonic transducer array. These results show that large sub-array has good direction property when the main frequency of detector is low. However it is contrary for high frequency of ultrasonic detector. This will be significative in photoacoustic signal detection and image reconstruction.

Compressive sensing photoacoustic imaging based on multi-view error gradient fusion

Compressive sensing photoacoustic imaging (PAI) is an emerging method for photoacoustic signal sampling and image reconstruction. Based on the method, the high-imaging rate and low-system cost can be achieved. Unfortunately, artefacts exist in the reconstructed images and appear heavier if the measurement is fewer. The artefacts appear at different pixels when images are observed from different angles, and can be rejected by the fusion of multi-view images. In this study, a multi-view image fusion method based on error gradient is proposed. The theory of compressive sensing PAI is introduced firstly. Then a feasible measurement scheme based on the digital micromirror device is constructed. Subsequently, error gradient of the reconstructed image is defined and the fusion rule based on error gradient is made. Finally, the proposed method is testified by the simulations, in which images observed from 0 and 90° are used to take the fusion. Simulation results demonstrate that the image artefacts can be reduced effectively by the proposed method.

Frequency-domain photoacoustic phased array probe for biomedical imaging applications

We report the development of a frequency-domain biomedical photoacoustic imaging system that utilizes a continuous-wave laser source with a custom intensity modulation pattern, ultrasonic phased array for signal detection, and processing coupled with a beam-forming algorithm for reconstruction of photoacoustic correlation images. Sensitivity to optical contrast was demonstrated using tissue-mimicking phantoms and in-vivo tissue samples.

Photoacoustic image reconstruction from few-detector and limited-angle data

Photoacoustic tomography (PAT) is an emerging non-invasive imaging technique with great potential for a wide range of biomedical imaging applications. However, the conventional PAT reconstruction algorithms often provide distorted images with strong artifacts in cases when the signals are collected from few measurements or over an aperture that does not enclose the object. In this work, we present a total-variation-minimization (TVM) enhanced iterative reconstruction algorithm that can provide excellent photoacoustic image reconstruction from few-detector and limited-angle data. The enhancement is confirmed and evaluated using several phantom experiments.

Image reconstruction in photoacoustic tomography involving layered acoustic media

Photoacoustic tomography (PAT), also known as thermoacoustic or optoacoustic tomography, is a rapidly emerging biomedical imaging technique that combines optical image contrast with ultrasound detection principles. Most existing reconstruction algorithms for PAT assume the object of interest possesses homogeneous acoustic properties. The images produced by such algorithms can contain significant distortions and artifacts when the object's acoustic properties are spatially variant. In this work, we establish an image reconstruction formula for PAT applications in which a planar detection surface is employed and the to-be-imaged optical absorber is embedded in a known planar layered acoustic medium. The reconstruction formula is exact in a mathematical sense and accounts for multiple acoustic reflections between the layers of the medium. Computer-simulation studies are conducted to demonstrate and investigate the proposed method.

Numerical modeling of photoacoustic imaging of brain tumors.

Photoacoustic imaging has shown great promise for medical imaging, where optical energy absorption by blood haemoglobin is used as the contrast mechanism. A numerical method has been developed for the in silico assessment of the photoacoustic image reconstruction of the brain. Image segmentation techniques were used to prepare a digital phantom from MR images. Then, light transport through brain tissue was modeled using the finite element approach. The resulting acoustic pressure was then estimated by pulsed photoacoustics considerations. The forward acoustic wave propagation was modeled by linearized coupled first order wave equations and solved by the acoustic k-space method. Since skull bone is an elastic solid and strongly attenuates ultrasound (due to scattering and absorption), a k-space method was developed for elastic media. To model scattering effects, a new approach was introduced based on propagation in random media. In addition, absorption effects were incorporated using a power law. Finally, the acoustic pressure was reconstructed using the k-space time reversal technique. The simulations were run in three dimensions to produce the photoacoustic tomogram of a brain tumor. The results show that relying on optical energy absorption by blood hemoglobin as the contrast mechanism, as is the current practice, leads to poor image quality.

Automatic sound speed selection in photoacoustic image reconstruction using an autofocus approach

The reconstruction of images in photoacoustic tomography is reliant on specifying the speed of sound within the propagation medium. However, for in vivo imaging, this value is not normally accurately known. Here, an autofocus approach for automatically selecting the sound speed is proposed. This is based on maximizing the sharpness of the reconstructed image as quantified by a focus function. Several focus functions are investigated, and their performance is discussed. The method is demonstrated using phantom measurements made in a medium with a known sound speed and in vivo measurements of the vasculature in the flank of an adult mouse.

Photoacoustic Imaging: An Emerging Optical Modality in Diagnostic and Theranostic Medicine

Photoacoustic imaging, also referred to optoacoustic imaging, is an emerging optical imaging technique that is capable of providing both structural and functional optical information of tissues up to several centimeters deep with scalable ultrasound resolution. The combination of ultrasound spatial resolution and intrinsic rich optical contrast in cancer / inflammatory tissues allow photoacoustic imaging a promising early detection tool in diagnostic medicine. At the same time, the availability of various optical absorbing nanostructures extensively studied in targeted drug delivery extends the capability of photoacoustic imaging to theranostic medicine, where functionalized nanostructures provide photoacoustic imaging contrast and targeting moieties / drug carrier for targeted drug delivery. In this paper, we provide a review of the photoacoustic imaging technique for studies in diagnostic and theranostic medicine. The technical consideration for photoacoustic imaging systems and reconstruction algorithms of structural / quantitative photoacoustic imaging have been introduced. A review of the photoacoustic imaging in breast cancer detection and osteoarthritis evaluation is included in the section of photoacoustic applications in diagnostic medicine, where patient subjects have been already recruited and photoacoustically evaluated. At the end of this paper, a brief review of optical controlled drug release and photoacoustic evaluation is presented as a view to the effort of combining laser induced photoacoustic imaging with laser controlled drug delivery / release in theranostic medicine.

Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm

The photoacoustic tomography (PAT) method, based on compressive sensing (CS) theory, requires that, for the CS reconstruction, the desired image should have a sparse representation in a known transform domain. However, the sparsity of photoacoustic signals is destroyed because noises always exist. Therefore, the original sparse signal cannot be effectively recovered using the general reconstruction algorithm. In this study, Bayesian compressive sensing (BCS) is employed to obtain highly sparse representations of photoacoustic images based on a set of noisy CS measurements. Results of simulation demonstrate that the BCS-reconstructed image can achieve superior performance than other state-of-the-art CS-reconstruction algorithms.

Photoacoustic tomography in absorbing acoustic media using time reversal

The reconstruction of photoacoustic images typically neglects the effect of acoustic absorption on the measured time domain signals. Here, a method to compensate for acoustic absorption in photoacoustic tomography is described. The approach is based on time-reversal image reconstruction and an absorbing equation of state which separately accounts for acoustic absorption and dispersion following a frequency power law. Absorption compensation in the inverse problem is achieved by reversing the absorption proportionality coefficient in sign but leaving the equivalent dispersion parameter unchanged. The reconstruction is regularized by filtering the absorption and dispersion terms in the spatial frequency domain using a Tukey window. This maintains the correct frequency dependence of these parameters within the filter pass band. The method is valid in one, two and three dimensions, and for arbitrary power law absorption parameters. The approach is verified through several numerical experiments. The reconstruction of a carbon fibre phantom and the vasculature in the abdomen of a mouse are also presented. When absorption compensation is included, a general improvement in the image magnitude and resolution is seen, particularly for deeper features.

Exact reconstruction in photoacoustic tomography with circular integrating detectors II: Spherical geometry

Illuminating tissue with pulsed electromagnetic waves generates acoustic waves inside an object which can be measured and converted into a three-dimensional (3d) image. This text is concerned with a two-step reconstruction method where the acoustic pressure is measured with circular integrating detectors. In the first step, reconstruction formulas for some kind of projection of the source distribution are derived; in the second step, an inversion formula for a circular radon transform on the sphere is developed. Copyright © 2010 John Wiley & Sons, Ltd.

SU‐GG‐I‐168: Image Reconstruction in an Attenuating Medium with Two Different Attenuation Coefficients Using Photoacoustic Tomography

Purpose: The goal of this research is to incorporate the effect of attenuation of the surrounding medium and accurately reconstruct the optical absorption distribution of the photoacoustic source. Method and Materials: Photoacoustic tomography (PAT) reconstructs an image of the optical absorption of an object using the pressure signals that are generated when the object is illuminated via pulsed electromagnetic radiation. The effect of ultrasonic attenuation can be significant since photoacoustic tomography uses broadband detection and the ultrasonic attenuation varies with frequency. Previous studies have related the detected pressure to the optical absorption coefficient when there is uniform attenuation. In this work, we specifically consider the practically important problem of an photoacoustic source embedded in a medium (such as tissue) with an attenuation coefficient, surrounded by a matching medium (such as water) with a different attenuation coefficient. The photoacoustic pressure that is measured by the detector in this case is not directly related to the optical absorption coefficient of the source. We have derived an analytical expression relating the photoacoustic pressure in the contact plane to the pressure in the detector plane. We can then reconstruct an image using the calculated pressure on the contact plane and the standard image reconstruction techniques for PAT. Results: Preliminary results in 2D suggest that the analytic expression that we derived to relate the photoacoustic pressure on the detection plane with that in the contact plane provides a suitable method for obtaining the photoacoustic source lying in an attenuating medium. Conclusion: The attenuation effect of the surrounding medium have been incorporated into image reconstruction in photoacoustic tomography. This work will be useful to accurately reconstruct the image in PAT when the attenuation coefficient of the object (such as tumor) differs from that of the surrounding medium (healthy tissue).

Transport-based quantitative photoacoustic tomography: simulations and experiments

In this paper we describe a method for quantitative photoacoustic tomography (qPAT) based on the photon radiative transfer equation (RTE) coupled with the Helmholtz photoacoustic wave equation. Considerable simulations and tissue-like phantom experiments are conducted to evaluate transport-based qPAT in comparison with diffusion-based qPAT. In these comparative simulations and experiments, we systematically examine the effects of the ratio of μa/μ′s (absorption/reduced scattering coefficient), the anisotropy factor (g) and the imaging domain size on the transport- and diffusion-based photoacoustic image reconstruction. The results obtained show that transport-based qPAT allows for clearly more accurate recovery of the absolute absorption coefficient images of heterogeneous media over diffusion-based qPAT for all the cases examined and provides considerably improved image quality for cases where the photon diffusion approximation (DA) is invalid.

Reconstruction of high quality photoacoustic tomography with a limited-view scanning

The goal of this work is to resolve the limited-view problem of photoacoustic tomography (PAT). We report a two-loop iteration method to inverse the photoacoustic sources from the measured photoacoustic signals. PAT reconstruction with this method does not depend on the detection path. Therefore, the proposed method can provide recognizable image even when the detector only scans a small angle (about 20 degrees approximately 30 degrees). The comparison with the delay-and-sum method shows the advantage of the proposed method in reconstructing image from incomplete data.

Image reconstruction in photoacoustic tomography with variable speed of sound using a higher-order geometrical acoustics approximation

Previous research correcting for variable speed of sound in photoacoustic tomography (PAT) based on a generalized radon transform (GRT) model assumes first-order geometrical acoustics (GA) approximation. In the GRT model, the pressure is related to the optical absorption, in an acoustically inhomogeneous medium, through integration over nonspherical isochronous surfaces. Previous research based on the GRT model assumes that the path taken by acoustic rays is linear and neglects amplitude perturbations to the measured pressure. We have derived a higher-order GA expression that takes into account the first-order effect in the amplitude of the measured signal and higher-order perturbation to the travel times. The higher-order perturbation to travel time incorporates the effect of ray bending. Incorrect travel times can lead to image distortion and blurring. These corrections are expected to impact image quality and quantitative PAT. We have previously shown that travel-time corrections in 2-D suggest that perceivable differences in the isochronous surfaces can be seen when the second-order travel-time perturbations are taken into account with a 10% speed-of-sound variation. In this work, we develop iterative image reconstruction algorithms that incorporate this higher-order GA approximation assuming that the speed of sound map is known. We evaluate the effect of higher-order GA approximation on image quality and accuracy.

Effects of Different Imaging Models on Least-Squares Image Reconstruction Accuracy in Photoacoustic Tomography

In the classic formulation of photoacoustic tomography (PAT), two distinct descriptions of the imaging model have been employed for developing reconstruction algorithms. We demonstrate that the numerical and statistical properties of unweighted least-squares reconstruction algorithms associated with each imaging model are generally very different. Specifically, some PAT reconstruction algorithms, including many of the iterative algorithms previously explored, do not work directly with the raw measured pressure wavefields, but rather with an integrated data function that is obtained by temporally integrating the photoacoustic wavefield. The integration modifies the statistical distribution of the data, introducing statistical correlations among samples. This change is highly significant for iterative algorithms, many of which explicitly or implicitly seek to minimize a statistical cost function. In this work, we demonstrate that iterative reconstruction by least-squares minimization yields better resolution-noise tradeoffs when working with the raw pressure data than with the integrated data commonly employed. In addition, we demonstrate that the raw-data based approach is less sensitive to certain deterministic errors, such as dc offset errors.

Quantitative three-dimensional photoacoustic tomography of the finger joints: phantom studies in a spherical scanning geometry

In this paper, we present a series of phantom experiments that aim to systematically evaluate the possibility of quantitative three-dimensional (3D) photoacoustic imaging of the finger joints in a spherical scanning geometry. The 3D absorption coefficient images of the joint-mimicking phantoms are obtained using our finite-element-based photoacoustic image reconstruction algorithm coupled with the photon diffusion equation. The results show that a 1 mm thick ‘cartilage’ can be accurately differentiated from the ‘bones’ with a 1 MHz transducer. In addition, the absorption coefficient of the ‘cartilage’ can be effectively recovered when this optical property is varied from 0.015 to 0.04 mm−1. The phantom images shown in this paper suggest that 3D photoacoustic tomography in a spherical scanning geometry has the potential to image a realistic human joint.