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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: closed (30 April 2019) | Viewed by 41125

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Prof. Dr. Xueding Wang

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Department of Biomedical Engineering, University Michigan Ann Arbor, Ann Arbor, MI, USA
Interests: photoacoustic imaging; biomedical ultrasound
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Xinmai Yang

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Department of Mechanical Engineering, University of Kansas, Lawrence, KS, USA
Interests: photoacoustic imaging; biomedical ultrasound
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Prof. Dr. Xose Luis Dean-Ben

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Institute for Biological and Medical Imaging, Helmholtz Zentrum Munich & Technical University of Munich, 81675 Munich, Germany
Interests: photoacoustic imaging; biomedical ultrasound
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Special Issue Information

Dear Colleagues,

Photoacoustic (or optoacoustic) imaging, including photoacoustic tomography (PAT) and photoacoustic microscopy (PAM), is an emerging imaging modality with great clinical potential. PAI’s deep tissue penetration and fine spatial resolution also hold great promise for visualizing physiology and pathology at the molecular level. PAI combines optical contrast with ultrasonic resolution, and is capable of imaging at depths of up to 7 cm with a real-time scalable spatial resolution of 10 to 500 µm. PAI has demonstrated applications in brain imaging and cancer imaging such breast cancer, prostate cancer, oval cancer etc. This Special Issue focuses on the novel technological developments and pre-clinical and clinical biomedical applications of PAI. Topics include, but are not limited to:

Brain imaging
Cancer imaging
Image reconstruction
Quantitative imaging
Light source and delivery for PAI
Photoacoustic detector
Nanoparticles designed for PAI
Photoacoustic molecular imaging
Photoacoustic spectroscopy

Prof. Dr. Xueding Wang
Prof. Dr. Xinmai Yang
Dr. Xose Luis Dean-Ben
Guest Editors

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Keywords

photoacoustic imaging
photoacoustic tomography
photoacoustic microscopy
molecular imaging
laser
ultrasound
nanoparticle
cancer
brain

Published Papers (12 papers)

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2 pages, 140 KiB

Open AccessEditorial

Special Issue on Photoacoustic Tomography

by Xueding Wang, Xinmai Yang and Xose Luis Dean-Ben

Appl. Sci. 2019, 9(19), 4186; https://doi.org/10.3390/app9194186 - 08 Oct 2019

Viewed by 1802

Abstract

Biomedical photoacoustic (or optoacoustic) tomography (PAT), or more generally, photoacoustic imaging (PAI), has been an active area of study and development in the last two decades [...] Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

Research

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12 pages, 2743 KiB

Open AccessArticle

Photoacoustic Tomography with a Ring Ultrasound Transducer: A Comparison of Different Illumination Strategies

by Naser Alijabbari, Suhail S. Alshahrani, Alexander Pattyn and Mohammad Mehrmohammadi

Appl. Sci. 2019, 9(15), 3094; https://doi.org/10.3390/app9153094 - 31 Jul 2019

Cited by 16 | Viewed by 2926

Abstract

Photoacoustic (PA) imaging is a methodology that uses the absorption of short laser pulses by endogenous or exogenous chromophores within human tissue, and the subsequent generation of acoustic waves acquired by an ultrasound (US) transducer, to form an image that can provide functional and molecular information. Amongst the various types of PA imaging, PA tomography (PAT) has been proposed for imaging pathologies such as breast cancer. However, the main challenge for PAT imaging is the deliverance of sufficient light energy horizontally through an imaging cross-section as well as vertically. In this study, three different illumination methods are compared for a full-ring ultrasound (US) PAT system. The three distinct illumination setups are full-ring, diffused-beam, and point source illumination. The full-ring system utilizes a cone mirror and parabolic reflector to create the ringed-shaped beam for PAT, while the diffuse scheme uses a light diffuser to expand the beam, which illuminates tissue-mimicking phantoms. The results indicate that the full-ring illumination is capable of providing a more uniform fluence irrespective of the vertical depth of the imaged cross-section, while the point source and diffused illumination methods provide a higher fluence at regions closer to the point of entry, which diminishes with depth. In addition, a set of experiments was conducted to determine the optimum position of ring-illumination with respect to the position of the acoustic detectors to achieve the highest signal-to-noise ratio. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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9 pages, 1045 KiB

Open AccessArticle

Self-Gated Respiratory Motion Rejection for Optoacoustic Tomography

by Avihai Ron, Neda Davoudi, Xosé Luís Deán-Ben and Daniel Razansky

Appl. Sci. 2019, 9(13), 2737; https://doi.org/10.3390/app9132737 - 06 Jul 2019

Cited by 20 | Viewed by 3040

Abstract

Respiratory motion in living organisms is known to result in image blurring and loss of resolution, chiefly due to the lengthy acquisition times of the corresponding image acquisition methods. Optoacoustic tomography can effectively eliminate in vivo motion artifacts due to its inherent capacity for collecting image data from the entire imaged region following a single nanoseconds-duration laser pulse. However, multi-frame image analysis is often essential in applications relying on spectroscopic data acquisition or for scanning-based systems. Thereby, efficient methods to correct for image distortions due to motion are imperative. Herein, we demonstrate that efficient motion rejection in optoacoustic tomography can readily be accomplished by frame clustering during image acquisition, thus averting excessive data acquisition and post-processing. The algorithm’s efficiency for two- and three-dimensional imaging was validated with experimental whole-body mouse data acquired by spiral volumetric optoacoustic tomography (SVOT) and full-ring cross-sectional imaging scanners. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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17 pages, 14103 KiB

Open AccessArticle

Accelerated Correction of Reflection Artifacts by Deep Neural Networks in Photo-Acoustic Tomography

by Hongming Shan, Ge Wang and Yang Yang

Appl. Sci. 2019, 9(13), 2615; https://doi.org/10.3390/app9132615 - 28 Jun 2019

Cited by 23 | Viewed by 3286

Abstract

Photo-Acoustic Tomography (PAT) is an emerging non-invasive hybrid modality driven by a constant yearning for superior imaging performance. The image quality, however, hinges on the acoustic reflection, which may compromise the diagnostic performance. To address this challenge, we propose to incorporate a deep neural network into conventional iterative algorithms to accelerate and improve the correction of reflection artifacts. Based on the simulated PAT dataset from computed tomography (CT) scans, this network-accelerated reconstruction approach is shown to outperform two state-of-the-art iterative algorithms in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) in the presence of noise. The proposed network also demonstrates considerably higher computational efficiency than conventional iterative algorithms, which are time-consuming and cumbersome. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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8 pages, 1280 KiB

Open AccessArticle

Reconstruction of Photoacoustic Tomography Inside a Scattering Layer Using a Matrix Filtering Method

by Wei Rui, Zhipeng Liu, Chao Tao and Xiaojun Liu

Appl. Sci. 2019, 9(10), 2071; https://doi.org/10.3390/app9102071 - 20 May 2019

Cited by 3 | Viewed by 2152

Abstract

Photoacoustic (PA) tomography (PAT) has potential for use in brain imaging due to its rich optical contrast, high acoustic resolution in deep tissue, and good biosafety. However, the skull often poses challenges for transcranial brain imaging. The skull can cause severe distortion and attenuation of the phase and amplitude of PA waves, which leads to poor resolution, low contrast, and strong noise in the images. In this study, we propose an image reconstruction method to recover the PA image insider a skull-like scattering layer. This method reduces the scattering artifacts by combining a correlation matrix filter and a time reversal operator. Both numerical simulations and PA imaging experiments demonstrate that the proposed approach effectively improves the image quality with less speckle noise and better signal-to-noise ratio. The proposed method may improve the quality of PAT in a complex acoustic scattering environment, such as transcranial brain imaging. Full article

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14 pages, 3813 KiB

Open AccessArticle

3D Photoacoustic Tomography System Based on Full-View Illumination and Ultrasound Detection

by Mingjian Sun, Depeng Hu, Wenxue Zhou, Yang Liu, Yawei Qu and Liyong Ma

Appl. Sci. 2019, 9(9), 1904; https://doi.org/10.3390/app9091904 - 09 May 2019

Cited by 5 | Viewed by 3711

Abstract

A 3D photoacoustic computed tomography (3D-PACT) system based on full-view illumination and ultrasound detection was developed and applied to 3D photoacoustic imaging of several phantoms. The system utilized an optics cage design to achieve full-view uniform laser illumination and completed 3D scanning with the rotation of a dual-element transducer (5 MHz) and the vertical motion of imaging target, which obtains the best solution in the mutual restriction relation between cost and performance. The 3D-PACT system exhibits a spatial resolution on the order of 300 μm, and the imaging area can be up to 52 mm in diameter. The transducers used in the system provides tomography imaging with large fields of view. In addition, the coplanar uniform illumination and acoustic detection configuration based on a quartz bowl greatly enhances the efficiency of laser illumination and signal detection, making it available for use on samples with irregular surfaces. Performance testing and 3D photoacoustic experiments on various phantoms verify that the system can perform 3D photoacoustic imaging on targets with complex surfaces or large sizes. In future, efforts will be made to achieve full-body 3D tomography of small animals and a multimodal 3D imaging system. Full article

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16 pages, 2401 KiB

Open AccessArticle

Full Field Inversion in Photoacoustic Tomography with Variable Sound Speed

by Gerhard Zangerl, Markus Haltmeier, Linh V. Nguyen and Robert Nuster

Appl. Sci. 2019, 9(8), 1563; https://doi.org/10.3390/app9081563 - 15 Apr 2019

Cited by 7 | Viewed by 3045

Abstract

To accelerate photoacoustic data acquisition, in [R. Nuster, G. Zangerl, M. Haltmeier, G. Paltauf (2010). Full field detection in photoacoustic tomography. Optics express, 18(6), 6288–6299] a novel measurement and reconstruction approach has been proposed, where the measured data consist of projections of the full 3D acoustic pressure distribution at a certain time instant T. Existing reconstruction algorithms for this kind of setup assume a constant speed of sound. This assumption is not always met in practice and thus can lead to erroneous reconstructions. In this paper, we present a two-step reconstruction method for full field detection photoacoustic tomography that takes variable speed of sound into account. In the first step, by applying the inverse Radon transform, the pressure distribution at the measurement time is reconstructed point-wise from the projection data. In the second step, a final time wave inversion problem is solved where the initial pressure distribution is recovered from the known pressure distribution at time T. We derive an iterative solution approach for the final time wave inversion problem and compute the required adjoint operator. Moreover, as the main result of this paper, we derive its uniqueness and stability. Our numerical results demonstrate that the proposed reconstruction scheme is fast and stable, and that ignoring sound speed variations significantly degrades the reconstruction. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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10 pages, 2190 KiB

Open AccessArticle

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

by Mohsin Zafar, Karl Kratkiewicz, Rayyan Manwar and Mohammad Avanaki

Appl. Sci. 2019, 9(3), 374; https://doi.org/10.3390/app9030374 - 22 Jan 2019

Cited by 52 | Viewed by 4536

Abstract

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 360° 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. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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12 pages, 1868 KiB

Open AccessArticle

Adipocyte Size Evaluation Based on Photoacoustic Spectral Analysis Combined with Deep Learning Method

by Xiang Ma, Meng Cao, Qinghong Shen, Jie Yuan, Ting Feng, Qian Cheng, Xueding Wang, Alexandra R. Washabaugh, Nicki A. Baker, Carey N. Lumeng and Robert W. O’Rourke

Appl. Sci. 2018, 8(11), 2178; https://doi.org/10.3390/app8112178 - 07 Nov 2018

Cited by 7 | Viewed by 2699

Abstract

Adipocyte size, i.e., the cell area of adipose tissue, is correlated directly with metabolic disease risk in obese humans. This study proposes an approach of processing the photoacoustic (PA) signal power spectrum using a deep learning method to evaluate adipocyte size in human adipose tissue. This approach has the potential to provide noninvasive assessment of adipose tissue dysfunction, replacing traditional invasive methods of evaluating adipose tissue via biopsy and histopathology. A deep neural network with fully connected layers was used to fit the relationship between PA spectrum and average adipocyte size. Experiments on human adipose tissue specimens were performed, and the optimal parameters of the deep learning method were applied to establish the relationship between the PA spectrum and average adipocyte size. By studying different spectral bands in the entire spectral range using the deep network, a spectral band mostly sensitive to the adipocyte size was identified. A method of combining all frequency components of PA spectrum was tested to achieve a more accurate evaluation. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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9 pages, 1828 KiB

Open AccessArticle

Biomedical Photoacoustic Imaging Optimization with Deconvolution and EMD Reconstruction

by Chengwen Guo, Yingna Chen, Jie Yuan, Yunhao Zhu, Qian Cheng and Xueding Wang

Appl. Sci. 2018, 8(11), 2113; https://doi.org/10.3390/app8112113 - 01 Nov 2018

Cited by 9 | Viewed by 3517

Abstract

A photoacoustic (PA) signal of an ideal optical absorbing particle is a single N-shape wave. PA signals are a combination of several individual N-shape waves. However, the N-shape wave basis leads to aliasing between adjacent micro-structures, which deteriorates the quality of final PA images. In this paper, we propose an image optimization method by processing raw PA signals with deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent deconvolution kernel, which is measured in advance. EMD is subsequently adopted to further process the PA signals adaptively with two restrictive conditions: positive polarity and spectrum consistency. With this method, signal aliasing is alleviated, and the micro-structures and detail information, previously buried in the reconstructing images, can now be revealed. To validate our proposed method, numerical simulations and phantom studies are implemented, and reconstructed images are used for illustration. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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13 pages, 4273 KiB

Open AccessArticle

A Novel Dictionary-Based Image Reconstruction for Photoacoustic Computed Tomography

by Parsa Omidi, Mohsin Zafar, Moein Mozaffarzadeh, Ali Hariri, Xiangzhi Haung, Mahdi Orooji and Mohammadreza Nasiriavanaki

Appl. Sci. 2018, 8(9), 1570; https://doi.org/10.3390/app8091570 - 06 Sep 2018

Cited by 61 | Viewed by 4682

Abstract

One of the major concerns in photoacoustic computed tomography (PACT) is obtaining a high-quality image using the minimum number of ultrasound transducers/view angles. This issue is of importance when a cost-effective PACT system is needed. On the other hand, analytical reconstruction algorithms such as back projection (BP) and time reversal, when a limited number of view angles is used, cause artifacts in the reconstructed image. Iterative algorithms provide a higher image quality, compared to BP, due to a model used for image reconstruction. The performance of the model can be further improved using the sparsity concept. In this paper, we propose using a novel sparse dictionary to capture important features of the photoacoustic signal and eliminate the artifacts while few transducers is used. Our dictionary is an optimum combination of Wavelet Transform (WT), Discrete Cosine Transform (DCT), and Total Variation (TV). We utilize two quality assessment metrics including peak signal-to-noise ratio and edge preservation index to quantitatively evaluate the reconstructed images. The results show that the proposed method can generate high-quality images having fewer artifacts and preserved edges, when fewer view angles are used for reconstruction in PACT. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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16 pages, 1094 KiB

Open AccessArticle

A Single Simulation Platform for Hybrid Photoacoustic and RF-Acoustic Computed Tomography

by Christopher Fadden and Sri-Rajasekhar Kothapalli

Appl. Sci. 2018, 8(9), 1568; https://doi.org/10.3390/app8091568 - 06 Sep 2018

Cited by 18 | Viewed by 4736

Abstract

In recent years, multimodal thermoacoustic imaging has demonstrated superior imaging quality compared to other emerging modalities. It provides functional and molecular information, arising due to electromagnetic absorption contrast, at ultrasonic resolution using inexpensive and non-ionizing imaging methods. The development of optical- as well as radio frequency (RF)-induced thermoacoustic imaging systems would benefit from reliable numerical simulations. To date, most numerical models use a combination of different software in order to model the hybrid thermoacoustic phenomenon. Here, we demonstrate the use of a single open source finite element software platform (ONELAB) for photo- and RF-acoustic computed tomography. The solutions of the optical diffusion equation, frequency domain Maxwell’s equations, and time-domain wave equation are used to solve the optical, electromagnetic, and acoustic propagation problems, respectively, in ONELAB. The results on a test homogeneous phantom and an approximate breast phantom confirm that ONELAB is a very effective software for both photo- and RF-acoustic simulations, and invaluable for developing new reconstruction algorithms and hardware systems. Full article

(This article belongs to the Special Issue Photoacoustic Tomography (PAT))

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