Denoising method for photoacoustic microscopy using deep learning

Photoacoustic (PA) tomography enables imaging of optical absorption property in deep scattering tissue by listening to the PA wave. However, it is an open challenge that the conversion efficiency from light to sound based on PA effect is extremely low. The consequence is the poor signal-to-noise ratio (SNR) of PA signal especially in scenarios of low laser power and deep penetration. The conventional way to improve PA signal's SNR is data averaging, which however severely limits the imaging speed. In this paper, we propose a new adaptive wavelet threshold de-noising (aWTD) algorithm, and apply it in photoacoustic tomography to increase the PA signal's SNR without sacrificing the signal fidelity and imaging speed. PA image quality in terms of contrast is also significantly improved. The proposed method provides the potential to develop real-time low-cost PA tomography system with low-power laser source.

Photoacoustic (PA) imaging holds great promise for preclinical research and clinical practice. However, most studies rely on the laser wavelength in the first near-infrared (NIR) window (NIR-I, 650-950 nm), while few studies have been exploited in the second NIR window (NIR-II, 1000-1700 nm), mainly due to the lack of NIR-II absorbing contrast agents. We herein report the synthesis of a broadband absorbing PA contrast agent based on semiconducting polymer nanoparticles (SPN-II) and apply it for PA imaging in NIR-II window. SPN-II can absorb in both NIR-I and NIR-II regions, providing the feasibility to directly compare PA imaging at 750 nm with that at 1064 nm. Because of the weaker background PA signals from biological tissues in NIR-II window, the signal-to-noise ratio (SNR) of SPN-II resulted PA images at 1064 nm can be 1.4-times higher than that at 750 nm when comparing at the imaging depth of 3 cm. The proof-of-concept application of NIR-II PA imaging is demonstrated in in vivo imaging of brain vasculature in living rats, which showed 1.5-times higher SNR as compared with NIR-I PA imaging. Our study not only introduces the first broadband absorbing organic contrast agent that is applicable for PA imaging in both NIR-I and NIR-II windows but also reveals the advantages of NIR-II over NIR-I in PA imaging.

Photoacoustic imaging is a hybrid imaging technique based on the photoacoustic effect. As a non-invasive and non-ionizing modality, photoacoustic imaging takes the both merits of the conventional acoustic imaging and optical imaging. Firstly, the contrast of photoacoustic imaging primarily depends on the optical absorption. The unique optical spectra of atoms and molecules makes optical methods to be a widely used modality to probe the molecular and chemical information of biological tissue. Therefore, photoacoustic imaging has its inherent advantage in high-contrast functional and physiological imaging of biological tissue, as well as the optical imaging method. Secondly, photoacoustic imaging has the high spatial resolution in deep tissue in comparison with the pure optical imaging method. Since the strongly optical scattering in biological tissue, pure optical imaging method is difficult to obtain the high-resolution image in the tissue deeper than ～1 mm. Whereas, acoustic wave suffers much less from scattering than optical wave, the acoustic scattering coefficient is about 2-3 orders of magnitude less than the optical scattering coefficient. Photoacoustic imaging can achieve a fine resolution in deep tissue, which equivalent to 1/200 of the imaging depth. Thirdly, non-ionizing radiation used for photoacoustic imaging is much safer than X-ray. Moreover, the low-temperature rises make photoacoustic imaging be safely used in live tissue. A laser-induced temperature rise of 1 mK yields an initial pressure of ～800 Pa in soft tissue. Such a sound pressure level has reached the sensitivities of typical ultrasonic transducers. Fourthly, photoacoustic imaging has the ability of extracting multiple contrasts, including biochemical parameter, biomechanical parameter, blood velocity distribution, tissue temperature, and microstructure information. Photoacoustic imaging can capture more specific and reliable information about the tissue structure, function, metabolism, molecule, and gene. As a result, photoacoustic imaging has become one of the fastest growing biomedical imaging techniques in the past decade.#br#In this review, we will explain photoacoustic effect and the principle of photoacoustic imaging. Then, we introduce the two classical photoacoustic imaging schemes, including photoacoustic tomography and photoacoustic microscopy. Their main specifications, such as resolution, are also preflents. We review the ability of photoacoustic imaging in extracting multiple contrasts and discuss their biomedicine applications. In addition, we also introduce the remarkable breakthroughs in super-resolution photoacoustic imaging. Finally, we look the further development and the limitations of photoacoustic imaging.

In recent years, the emerging non-harmful photoacoustic imaging technology has attracted extensive attention. This technology combines the advantages of high resolution and rich contrast of optical imaging with the advantages of high penetration depth of acoustic imaging. As a branch of photoacoustic imaging field, the photoacoustic microscopic technology, based on its unique focusing method, can achieve higher resolution, such as imaging of individual red blood cells, therefore, photoacoustic microscopy is widely used in the medical field. However, complex structure of the photoacoustic microscopy, expensive equipments of the photoacoustic microscopy, high cost of study of the photoacoustic microscopy, and complicated experimental operation steps cause the development of this technology to be limited. Therefore, it is necessary to combine simulation technology to build a photoacoustic microscopy simulation platform. In order to achieve this goal, in this paper, we build a simulation platform for photoacoustic microscopy based on K-Wave simulation toolbox. This simulation platform avoids the cost of equipment in real photoacoustic microscopy, which saves the research cost. Each module of the system (optical, Acoustics, etc.) can be easily adjusted and only need to modify the various system parameters to analyze the performance of the system. We measures the performance of the constructed photoacoustic microscopy by three-dimensional imaging of the blood vessel. A-Scan, B-Scan and C-Scan were simulated. The performance of the system was measured, with a lateral resolution of approximately 4.176 μm, an axial resolution of 27.056 μm. The establishment of the simulation platform has a significance for the theoretical research of photoacoustic microscopy and its application in biomedicine.

Photoacoustic imaging is a new biomedical imaging technology developed in recent years. It has the advantages of high resolution and sensitivity to the functional characteristics of biological tissues. However, whether for photoacoustic tomography or photoacoustic microscopy imaging, the imaging resolution depends on the frequency and bandwidth of the received ultrasonic signal. This leads to a large amount of data being collected under the Nyquist's law. So storage medium and DSP processor are under unprecedented pressure. The problem of large amount of data is usually solved by using compression. Therefore, the combination of compressed sensing theory and photoacoustic imaging can not only restore images with high quality, but also reduce the amount of data as much as possible. It saves storage space and the time of further data processing. This paper introduces signal sparsity and measurement matrix of compressed sensing theory briefly. The virtual photoacoustic imaging of blood vessels is carried out in the simulation environment constructed by the k-wave toolbox of MATLAB. The collected data are restored by using the gradient projection for sparse reconstruction. The results show that high quality photoacoustic imaging images can be reconstructed while a small amount of data is stored. The performance of the simulation platform is verified. And it is of great significance to solve the problem of high data volume of photoacoustic imaging.

<p>Over the last two and a half decades, photoacoustic (PA) imaging has become an important area of research in biomedical optics. Combining the high contrast of optical imaging with the high spatial resolution of ultrasound (US) imaging, PA imaging can simultaneously visualize anatomical structures while interrogating their functionality through multiwavelength optical spectroscopy. Alongside technological developments and imaging applications in optical and acoustic resolution PA imaging, a family of PA signal analysis techniques can extract additional information about the sample being imaged. This Tutorial focuses on techniques that rely on the analysis of PA signals in a manner similar to that in the complimentary field of quantitative ultrasound (QUS) imaging of soft tissues. In QUS, signal analysis techniques have been developed to analyze the US signals resulting from the scattering of many unresolved scatterers within the resolution volume of the imaging device. The implementation of these US techniques in PA can enable new applications in biomedicine beyond traditional anatomical PA imaging, further increasing the utilization and impact of this promising modality.</p>

Research on photoacoustic microscopy imaging based on photoacoustic transmission matrix with a digital micromirror device

Photoacoustic microscopy is an in vivo imaging technology based on the photoacoustic effect. It is widely used in various biomedical studies because it can provide high-resolution images while being label-free, safe, and harmless to biological tissue. Polygon-scanning is an effective scanning method in photoacoustic microscopy that can realize fast imaging of biological tissue with a large field of view. However, in polygon-scanning, fluctuations of the rotating motor speed and the geometric error of the rotating mirror cause image distortions, which seriously affect the photoacoustic-microscopy imaging quality. To improve the image quality of photoacoustic microscopy using polygon-scanning, an image correction method is proposed based on accurate ultrasound positioning. In this method, the photoacoustic and ultrasound imaging data of the sample are simultaneously obtained, and the angle information of each mirror used in the polygon-scanning is extracted from the ultrasonic data to correct the photoacoustic images. Experimental results show that the proposed method can significantly reduce image distortions in photoacoustic microscopy, with the image dislocation offset decreasing from 24.774 to 10.365 μm.

Photoacoustic imaging has shown great potential in guiding various minimally invasive procedures by providing complementary information to ultrasound imaging, visualising critical tissue targets as well as surgical tools such as metallic needles with rich optical contrast. The use of light emitting diodes (LEDs) as excitation sources further accelerates the clinical translation of this modality due to its favorable affordability, portability, and cost-efficiency but results in the degradation of image quality associated with low pulse energy. In this work, we propose a framework based on a modified U-Net to enhance the visualisation of clinical metallic needles with a commercial LED-based photoacoustic and ultrasound imaging system. This framework included the generation of semi-synthetic datasets combining both simulated data and in vivo measurements. Evaluation of the trained neural network was performed with needle insertions into a blood-vessel-mimicking phantom, and pork joint ex vivo tissue. This deep learning-based framework significantly enhanced the visualisation of the needle with photoacoustic imaging, achieving 4.3- and 3.2-times higher signal-to-noise ratios (SNRs) compared to conventional reconstructions, which could be helpful for guiding minimally invasive procedures.

As a functional imaging technique, photoacoustic imaging has the ability to produce high contrast and high resolution image. However, photoacoustic microscopy shows the disadvantage of limited depth of field, due to the strong focusing process. Only some part of the whole image is clear while some other information might be lost or misleading. To achieve a large volumetric and high resolution photoacoustic, we propose a depth-of-field expansion motivated multi-focus photoacoustic microscopy image fusion algorithm which fuses the information from imaging of different focal positions into single one to obtain all-in-focus image. To achieve this goal, the volumes obtained at different focus positions are sliced into 2D and the 2D image fusion based on cross bilateral filter is performed for correspond slices. Finally, 3D reconstruction can be performed on these fused slices. Experiment results show that our method can produce a 3D fusion result which maintains useful photoacoustic signal information for further analysis and visualization.

Photoacoustic (PA) imaging has become invaluable in preclinical and clinical research. Endoscopic PA imaging in particular has been explored as a noninvasive imaging modality to view vasculature and diagnose cancers in the digestive system. However, these feasibility studies are still limited to rodents or rabbits. Here, we develop a fully synchronized simultaneous ultrasound and photoacoustic microscopy system using two spectral bands (i.e., the visible and near-infrared) in both optical- and acoustic-resolution modes. We investigate the feasibility of imaging gastric vasculature in an ex vivo porcine model. The entire gastric wall, including the mucosa, submucosa, muscularis propria, and serosa, was excised from fresh porcine stomachs immediately followed by ultrasound and PA imaging being performed within a few hours of sacrifice. PA images of the mucosal vasculature were obtained at depths of 1.90 mm, which is a clinically significant accomplishment considering that the average thickness of the human mucosa is 1.26 mm. The layer structure of the stomach wall could be clearly distinguished in the overlaid PA and US images. Because gastric cancer starts from the mucosal surface and infiltrates into the submucosa, PA imaging can cover a clinically relevant depth in early gastric cancer diagnosis. We were able to detect mucosal vasculature in the entire mucosal layer, suggesting the potential utility of combined PA/US imaging in gastroenterology.

An inexpensive noncontact photoacoustic (PA) imaging system using a low-power continuous wave laser and a kilohertz-range microphone has been developed. The system operates in both optical and PA imaging modes and is designed to be compatible with conventional optical microscopes. Aqueous coupling fluids are not required for the detection of the PA signals; air is used as the coupling medium. The main component of the PA system is a custom designed PA imaging sensor that consists of an air-filled sample chamber and a resonator chamber that isolates a standard kilohertz frequency microphone from the input laser. A sample to be examined is placed on the glass substrate inside the chamber. A laser focused to a small spot by a 40 × objective onto the substrate enables generation of PA signals from the sample. Raster scanning the laser over the sample with micrometer-sized steps enables high-resolution PA images to be generated. A lateral resolution of 1.37 ?? ? m was achieved in this proof of concept study, which can be further improved using a higher numerical aperture objective. The application of the system was investigated on a red blood cell, with a noise-equivalent detection sensitivity of 43,887 hemoglobin molecules ( 72.88 × 10 ? 21 ?? mol or 72.88 zeptomol). The minimum pressure detectable limit of the system was 19.1 ?? ? Pa . This inexpensive, compact noncontact PA sensor is easily integrated with existing commercial optical microscopes, enabling optical and PA imaging of the same sample. Applications include forensic measurements, blood coagulation tests, and monitoring the penetration of drugs into human membrane.

Optical-resolution photoacoustic microscopy (OR-PAM) has been shown to be an excellent tool for high-resolution imaging of microvasculature, and quantitative analysis of the microvasculature can provide valuable information for the early diagnosis and treatment of various vascular-related diseases. In order to address the characteristics of weak signals, discontinuity and small diameters in photoacoustic microvascular images, we propose a method adaptive to the microvascular segmentation in photoacoustic images, including Hessian matrix enhancement and the morphological connection operators. The accuracy of our vascular segmentation method is quantitatively evaluated by the multiple criteria. To obtain more precise and continuous microvascular skeletons, an improved skeleton extraction framework based on the multistencil fast marching (MSFM) method is developed. We carried out in vivo OR-PAM microvascular imaging in mouse ears and subcutaneous hepatoma tumor model to verify the correctness and superiority of our proposed method. Compared with the previous methods, our proposed method can extract the microvascular network more completely, continuously and accurately, and provide an effective solution for the quantitative analysis of photoacoustic microvascular images with many small branches.

Photoacoustic tomography has been developed for in vivo functional, metabolic, molecular, and histologic imaging by physically combining optical and ultrasonic waves. Broad applications include early-cancer detection and brain imaging. High-resolution optical imaging—such as confocal microscopy, two-photon microscopy, and optical coherence tomography—is limited to superficial imaging within the optical diffusion limit (~1 mm in the skin) of the surface of scattering tissue. By synergistically combining light and sound, photoacoustic tomography conquers the optical diffusion limit and provides deep penetration at high ultrasonic resolution and high optical contrast. Photoacoustic tomography has two major embodiments: photoacoustic computed tomography and photoacoustic microscopy. In photoacoustic computed tomography, a pulsed broad laser beam illuminates the biological tissue to generate a small but rapid temperature rise, which leads to emission of ultrasonic waves due to thermoelastic expansion. The unscattered pulsed ultrasonic waves are then detected by ultrasonic transducers. High-resolution tomographic images of optical contrast are then formed through image reconstruction. In photoacoustic microscopy, a pulsed laser beam is delivered into the biological tissue to generate ultrasonic waves, which are then detected with a focused ultrasonic transducer to form a depth resolved 1D image. Raster scanning yields 3D high-resolution tomographic images. Super-depths beyond the optical diffusion limit have been reached with high spatial resolution. The annual conference on PAT has grown exponentially since early 2000 and become the largest in SPIE’s 20,000-attendee Photonics West since 2010.

Ultrasound (US) image guidance is widely used for minimally invasive procedures, but the invasive medical devices (such as metallic needles), especially their tips, can be poorly visualised in US images, leading to significant complications. Photoacoustic (PA) imaging is promising for visualising invasive devices and peripheral tissue targets. Light-emitting diodes (LEDs) acting as PA excitation sources facilitate the clinical translation of PA imaging, but the image quality is degraded due to the low pulse energy leading to insufficient contrast with needles at deep locations. In this paper, photoacoustic visualisation of clinical needles was enhanced by elastomeric nanocomposite coatings with superficial and interstitial illumination. Candle soot nanoparticle-polydimethylsiloxane (CSNP-PDMS) composites with high optical absorption and large thermal expansion coefficients were applied onto the needle exterior and the end-face of an optical fibre placed in the needle lumen. The excitation light was delivered at the surface by LED arrays and through the embedded optical fibre by a pulsed diode laser to improve the visibility of the needle tip. The performance was validated using an ex-vivo tissue model. An LED-based PA/US imaging system was used for imaging the needle out-of-plane and in-plane insertions over approach angles of 20 deg to 55 deg. The CSNP-PDMS composite conferred substantial visual enhancements on both the needle shaft and the tip, with an average of 1.7- and 1.6-fold improvements in signal-to-noise ratios (SNRs), respectively. With the extended light field involving extracorporeal and interstitial illumination and the highly absorbing coatings, enhanced visualisation of the needle shaft and needle tip was achieved with PA imaging, which could be helpful in current US-guided minimally invasive surgeries.