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This PDF file contains the front matter associated with SPIE Proceedings Volume 11923, including the Title Page, Copyright information, and Table of Contents.
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Image contrast in multispectral optoacoustic tomography can be reduced by electrical noise. We present a deep learning method to remove electrical noise from optoacoustic signals and thereby significantly enhance morphological and spectral contrast.
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We propose a “gradient filter” reconstruction scheme for solving the dynamic pharmacokinetic problem using fluorescence-photoacoustic tomography in a shape based framework. The proposed method is validated using cancer mimicking phantoms.
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Deblurring approach for band-limited sensors and broad laser pulse is studied. The backprojection and Tikhonov regularization algorithms were implemented for image reconstruction. Blurring can be removed significantly using the method presented here.
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Repetitively applied laser pulses are used for tissue heating and temperature measurement. The potential of model-based control techniques for temperature regulation by adjusting the energy of the heating pulses is explored.
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We present and validate a simulation package for simulating the signal generated from arbitrary acousto-optical interaction in scattering media. We further present an example on how the package can be used as a virtual lab.
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We study the effect of using weaker forms of data-fidelity terms in generalized Tikhonov regularization accounting for model uncertainties. We show that relaxed data-consistency conditions can be beneficial for integrating available prior knowledge.
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In this work, a computationally efficient forward model for photoacoustic tomography is presented. The approach is able to produce accurate photoacoustic images with significantly reduced computational cost compared to a conventional approach.
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In this work, the inverse problem problem of quantitative photoacoustic tomography is approached in a Bayesian framework. Modeling errors caused by an approximative light transport model are compensated by utilizing Bayesian approximation error modeling.
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We investigate resolution in photoacoustic tomography (PAT). Using Shannon theory, we investigate the theoretical resolution limit of sparse view PAT theoretically, and empirically demonstrate that all reconstruction methods used exceed this limit.
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In this work, use of perturbation Monte Carlo is extended to solving inverse problem of quantitative photoacoustic tomography. The approach is demonstrated feasible for estimating optical absorption and scattering distribution.
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Photoacoustic imaging (PAI) provides optical contrast at depth beyond the optical transport mean free path. From the generation of ultrasound by light absorption, images can be reconstructed at the acoustic resolution ( 100 μm) with a penetration of a few cm. The design of imaging systems often leads to limited view artifacts, where a part of the information needed for a complete reconstruction of the objects is missing. We theoretically show that a dynamic approach based on the analysis of fluctuations induced by blood flow can suppress visibility artefacts. We demonstrate the performance of 3D Photoacoustic Fluctuation imaging (PAFI) using a spherical array with limited number of channels (256
elements, 8 MHz) in the chicken embryo model. Due to the low number of channels, standard PAI reconstructions additionally suffer from a poor contrast, which is enhanced by 2 to 3-fold using PAFI. We present an implementation of simultaneous PAFI and Ultrasound Power Doppler and present some results with coupled flow direction evaluations and optical contrast. Photoacoustic fluctuation imaging overcomes many limitations of conventional imaging and will be further evaluated for in-vivo imaging.
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In conventional photoacoustics (PA) imaging, the finite size and limited-bandwidth of ultrasound transducers often lead to visibility artifacts resulting in a degraded image quality. We propose a reconstruction algorithm based on deep learning to address theses issues. An in vitro vasculature mimicking model has been used in order to show the capability of a conventional neural network to remove these artefacts in an experimental configuration. The deep learning algorithm is trained using couples of PA images and ground truth photographs. The uncertainty of the model prediction is estimated through the Monte Carlo dropout method allowing the display of a pixel-wise degree of confidence. Finally, the interest of using simulation data through transfer learning in order to reduce the size of the experimental dataset is investigated.
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Novel Instrumentation, Microscopy, and Detectors I
We report the development of a high-speed and non-invasive method for focusing light through scattering media using photoacoustic guidance. We demonstrated light focusing through an optical diffuser within ∼ 300 ms.
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Photoacoustic pump-probe excitation was used to generate a fluorophore-specific contrast in fluorescent proteins. The measured signals using pump-probe spectroscopy were found to correlate with the absorption and emission spectra of the protein.
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We introduce transparent TOBE CMUT arrays for multimodal imaging systems, combining ultrasound with photoacoustic and optical imaging systems. We designed and fabricated a 128-element lambda-pitch transducers with high transparency ranging from visible to near-infrared.
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Novel method for spatially coding ultrasonic detectors is described and experimentally demonstrated by in vivo Optoacoustic imaging of a mouse leg using a single detector, effectively transformed to a 2D detection array with 1763 elements.
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We present a multimodal imaging system that seamlessly integrates ultrasound imaging, photoacoustic imaging, and optical coherence tomography using a transparent ultrasonic transducer. We demonstrate the system’s use in imaging responses to mouse body in vivo.
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During retinal laser treatment with a single microsecond laser pulse in the range of 5-50 μs, the induced optoacoutics transients are used to determine the temperature rise and microbubble formation in case of appearance.
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Novel Instrumentation, Microscopy, and Detectors II
Our work was devoted to the experimental comparison of two ultra-wideband detectors based on PVDF piezofilms of different thickness demonstrating different quality of optoacoustic imaging of vessels in tumor and normal tissues.
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We developed a rotatable and compact tabletop photoacoustic tomograph with camera based optical ultrasound detection. The system's performance: achievable resolution of <100 μm and 3D imaging duration of less than 20s.
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Using off-axis heterodyne holography, we present acousto-optical measurements of two phantoms: a silicon (no decorrelation) and a gel phantom (decorrelation). Decorrelation of the two media show differing trends that need to be understood to move towards in-vivo imaging.
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We present the development of a forward-viewing optical-resolution photoacoustic endo-microscopy probe based on a multimode fibre via high-speed wavefront shaping. High-resolution 3D photoacoustic microscopy images of carbon fibres and red blood cells were obtained.
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Photoacoustic microscopy with whole-area, structured illumination instead of point by point scanning is demonstrated. Using Hadamard patterns in combination with a differential ghost imaging reconstruction yields images of a phantom at various depths.
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We present our work in modelling the effects of optical aberrations on Fabry-Perot pressure sensor performance, as well as experimental strategies to tackle said aberrations using adaptive optics and laser mode filtering.
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We propose a new opto-mechanical ultrasound sensor (OMUS) enabled by an innovative silicon photonics waveguide. We present experimental results up to 30 MHz, a 10-sensor array proof-of-concept and our latest findings.
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We developed a numerical phantom of a mouse’s head where we performed photothermal therapy on a tumor. Nanoparticles are numerically added and their effects are studied. The medium’s temperature was monitored using the photoacoustic technique.
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Through chemical modification we developed higher photoacoustic yield molecular contrast agents that will likely enable deep tissue photoacoustic imaging. This talk will be on design and characterization of these contrast agents.
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The possibilities of optoacoustic microscopy for comparison of vascular network of different tumor models as well as for investigation of tumor vessels response to radiation therapy were demonstrated.
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Using optoacoustic microscopy, a radiation-induced increase in the fragmentation of experimental tumor small vessels, as well as the formation of large hemoglobin-containing structures were revealed within first days after treatment.
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The study presents a LED-based optoacoustic system for estimating relative absorbers’ concentration in ink - gelatin phantoms. Results support that LED sources present high potential for the development of low-cost optoacoustic spectroscopy systems.
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We developed high-density spherical matrix array based on polyvinylidene difluoride films. Ultrawide bandwidth (0.3-38 MHz) and sub-millimeter sized elements enabled non-invasive cerebrovascular imaging of adult mouse with ~60 μm resolution.
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The total impulse response of a clinical optoacoustic system is characterized by combining experimentally acquired signals with a numerical model of the spatial impulse response, resulting in high-resolution images in clinical applications.
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The optoacoustic stimulation of the peripheral hearing organ activates the central hearing system. For the potential application in hearing aids, we additionally used an absorber on the tympanic membrane that increased the central neuronal activation.
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This work combines recent advances in Multispectral Optoacoustic Tomography and Ultrafast Ultrasound Doppler imaging to obtain simultaneous in vivo images of blood perfusion and oxygen saturation with a single imaging system on healthy mice kidneys.
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A phantom is developed to replicate the spatial distribution of optical and acoustic breast properties. Blood-carrying channels, with ability to tune oxygenation, make the phantom suited for investigating the capability to extract oxygen saturation.
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We propose a novel all-optical focused ultrasound detector for intravascular optoacoustic imaging and demonstrate its imaging capabilities experimentally; the detector has a bandwidth of more than 75MHz and a spatial resolution of at least 50μm.
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We develop a dual-modality imaging system for virtual histology in breast tumor specimens, augmenting depth-resolved scattering contrast from OCT with sub-cellular resolution and label-free molecular specificity from UV photoacoustic remote sensing.
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A comprehensive analysis using three machine-learning models for an AI-aided atopic dermatitis (AD) diagnosis and sub-classifying AD severities with 3D Raster Scanning Optoacoustic Mesoscopy (RSOM) images, extracted features from volumetric vascular structures and clinical information.
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We demonstrate the opportunities of the developed 3D optoacoustic image processing algorithm to characterize numerically the vasculature parameters in different applications including monitoring of tumor angiogenesis and assessing skin aging.
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Photoacoustic spectroscopy is a well-known spectroscopic method for gas detection. Exhaled breath contains volatile organic compounds (VOCs) as bio-markers of specific health condition. Detection and quantification of VOC bio-markers from exhaled breath can provide valuable information about the health status. We report the design and development of Photoacoustic spectroscopy setup and a preliminary study of the detection of certain standard VOCs.
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We present a laser induced ultrasound and the localization of cavitation bubbles using an optoacoustic spherical Ti/black-TiOx lens. Results demonstrate the possibility to localize cavitiesand secondary ablative effects into the subsurface tissue.
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To validate the accuracy of photoacoustic imaging in evaluating blood oxygen saturation is important. By reducing oxygen saturation and comparing that of photoacoustic imaging with control, the results confirm that photoacoustic imaging is accurate.
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CR760, a croconaine dye with excellent optical properties, was synthesized in a single step and subsequently nano-formulated for optoacoustic imaging and photothermal therapy of cancer.
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We present different approaches to improve the photostability of plasmonic nanoparticles, either by constraining their initial shape, or by enhancing their thermal coupling to the environment by lowering the corresponding interfacial resistance.
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We describe the implementation of hierarchical materials made of hydrophilic micro-droplets in a silicone continuous phase to mimic the interactions of bio-tissue with multiple physical agents, such as those implied in photoacoustic imaging.
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