2,459 research outputs found

    A triple-modality ultrasound computed tomography based on full-waveform data for industrial processes

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    Ultrasound Tomography for control of Batch Crystallization

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    Refraction-corrected ray-based inversion for three-dimensional ultrasound tomography of the breast

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    Ultrasound Tomography has seen a revival of interest in the past decade, especially for breast imaging, due to improvements in both ultrasound and computing hardware. In particular, three-dimensional ultrasound tomography, a fully tomographic method in which the medium to be imaged is surrounded by ultrasound transducers, has become feasible. In this paper, a comprehensive derivation and study of a robust framework for large-scale bent-ray ultrasound tomography in 3D for a hemispherical detector array is presented. Two ray-tracing approaches are derived and compared. More significantly, the problem of linking the rays between emitters and receivers, which is challenging in 3D due to the high number of degrees of freedom for the trajectory of rays, is analysed both as a minimisation and as a root-finding problem. The ray-linking problem is parameterised for a convex detection surface and three robust, accurate, and efficient ray-linking algorithms are formulated and demonstrated. To stabilise these methods, novel adaptive-smoothing approaches are proposed that control the conditioning of the update matrices to ensure accurate linking. The nonlinear UST problem of estimating the sound speed was recast as a series of linearised subproblems, each solved using the above algorithms and within a steepest descent scheme. The whole imaging algorithm was demonstrated to be robust and accurate on realistic data simulated using a full-wave acoustic model and an anatomical breast phantom, and incorporating the errors due to time-of-flight picking that would be present with measured data. This method can used to provide a low-artefact, quantitatively accurate, 3D sound speed maps. In addition to being useful in their own right, such 3D sound speed maps can be used to initialise full-wave inversion methods, or as an input to photoacoustic tomography reconstructions

    Photoacoustic Reporter Gene Imaging And Optical Coherence Computed Tomography

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    Advances in imaging technologies have always been the major driving forces for the evolution of biomedical research. Compared with other modalities, optical imaging possesses several prominent merits. Because light interacts with tissue at the microscopic level through many distinct physical mechanisms, optical methods allow sensitive exploration of various aspects of the life down to the single-molecule level. From the technical perspective, optical systems utilize safe non-ionizing radiation, could be implemented at relatively low cost, also have the potential to be miniaturized for portable or endoscopic applications. As a result, optical imaging tools are playing an increasingly important role in both laboratorial research and clinical practice. Among them, photoacoustic imaging: PAI) and optical coherence tomography: OCT) are the two fastest growing branches. PAI measures the laser-induced acoustic wave, and produces high-resolution images of the optically absorbing features of tissue at multiple length-scales. OCT detects singly backscattered photons, and enables real-time high-resolution in vivo biopsy of tissue up to an optical transport mean-free-path. My doctoral research is focused on developing three novel optical imaging techniques based on the spirits of PAI and OCT. In the first part of this study, we established a new paradigm to visualize gene expression in vivo based on optical absorption. In the post-genomic era, we are now being challenged to develop novel molecular imaging methods to identify the functions of genes. PAI can detect specific molecules according to their characteristic absorption spectra, thus is a promising candidate for molecular imaging of gene expression. The full potential of photoacoustic molecular imaging still remains to be explored. For the first time, we demonstrated imaging gene expression by PAI in living mice and rats, using a chromogenic lacZ/X-gal reporter gene system. We demonstrated the expression of the lacZ reporter gene can be detected by PAI as deep as 5 cm inside tissue. In addition, we showcased that PAI could follow gene expression from the microscopic to the macroscopic level. This work represents one of the pioneering efforts to extend photoacoustic methods for molecular imaging. In the second part of this study, we developed a novel multimodal microscope, called the integrated photoacoustic and optical coherence microscope: iPOM), which combines PAI and OCT in a single imaging platform. PAI is predominantly sensitive to optical absorption, while OCT exploits optical scattering. By combining their naturally complementary imaging contrasts, iPOM can provide comprehensive information about biological tissue. We designed and built a reflection-mode prototype of iPOM, which fuses optical-resolution photoacoustic microscopy with spectral-domain optical coherence tomography. The potential applications of iPOM in studying cutaneous and ocular microcirculation, and tissue engineering were demonstrated. Finally, we invented a new optical tomography, named optical coherence computed tomography: optical CCT), which overcomes several major limitations of OCT. OCT relies on singly backscattered photons to obtain high-resolution images. Its image quality degrades fast with the increase of the depth, because the multiply scattered photons quickly become dominant at a penetration larger than 500 &mum. As a result, OCT can only effectively penetrate ~1 mm into highly scattering tissue like skin. In addition, OCT is mainly sensitive to optical scattering, which does not reflect the molecular content of tissue directly. Optical CCT measures both singly and multiply scattered photons using a low-coherence interferometer. We make use of both types of photons by adopting a model-based reconstruction algorithm. The light-tissue interaction model was established using the time-resolved Monte Carlo method. The optical properties of the tissue were reconstructed from measurements by solving the inverse radiative transport problem under the first Born approximation. As a result, optical CCT could image deeper than OCT, and provide extra molecule-specific contrasts, such as optical absorption. We designed and built the first optical CCT system. In experiments, absorbing inclusions of 100 &mum diameter were imaged with consistent quality through a 2.6-mm-thick: equivalent to ~3 transport mean-free-paths) tissue-mimicking phantom

    Selected Papers from the 9th World Congress on Industrial Process Tomography

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    Industrial process tomography (IPT) is becoming an important tool for Industry 4.0. It consists of multidimensional sensor technologies and methods that aim to provide unparalleled internal information on industrial processes used in many sectors. This book showcases a selection of papers at the forefront of the latest developments in such technologies

    Photoacoustic imaging in biomedicine

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    Photoacoustic imaging (also called optoacoustic or thermoacoustic imaging) has the potential to image animal or human organs, such as the breast and the brain, with simultaneous high contrast and high spatial resolution. This article provides an overview of the rapidly expanding field of photoacoustic imaging for biomedical applications. Imaging techniques, including depth profiling in layered media, scanning tomography with focused ultrasonic transducers, image forming with an acoustic lens, and computed tomography with unfocused transducers, are introduced. Special emphasis is placed on computed tomography, including reconstruction algorithms, spatial resolution, and related recent experiments. Promising biomedical applications are discussed throughout the text, including (1) tomographic imaging of the skin and other superficial organs by laser-induced photoacoustic microscopy, which offers the critical advantages, over current high-resolution optical imaging modalities, of deeper imaging depth and higher absorptioncontrasts, (2) breast cancerdetection by near-infrared light or radio-frequency–wave-induced photoacoustic imaging, which has important potential for early detection, and (3) small animal imaging by laser-induced photoacoustic imaging, which measures unique optical absorptioncontrasts related to important biochemical information and provides better resolution in deep tissues than optical imaging

    Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distribution in Photoacoustic Computed Tomography: A numerical Investigation

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    Photoacoustic computed tomography (PACT) is a rapidly emerging bioimaging modality that seeks to reconstruct an estimate of the absorbed optical energy density within an object. Conventional PACT image reconstruction methods assume a constant speed-of-sound (SOS), which can result in image artifacts when acoustic aberrations are significant. It has been demonstrated that incorporating knowledge of an object's SOS distribution into a PACT image reconstruction method can improve image quality. However, in many cases, the SOS distribution cannot be accurately and/or conveniently estimated prior to the PACT experiment. Because variations in the SOS distribution induce aberrations in the measured photoacoustic wavefields, certain information regarding an object's SOS distribution is encoded in the PACT measurement data. Based on this observation, a joint reconstruction (JR) problem has been proposed in which the SOS distribution is concurrently estimated along with the sought-after absorbed optical energy density from the photoacoustic measurement data. A broad understanding of the extent to which the JR problem can be accurately and reliably solved has not been reported. In this work, a series of numerical experiments is described that elucidate some important properties of the JR problem that pertain to its practical feasibility. To accomplish this, an optimization-based formulation of the JR problem is developed that yields a non-linear iterative algorithm that alternatingly updates the two image estimates. Heuristic analytic insights into the reconstruction problem are also provided. These results confirm the ill-conditioned nature of the joint reconstruction problem that will present significant challenges for practical applications.Comment: 13 pages, submitted to IEEE Transactions on Computational Imagin
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