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Photoacoustic computed tomography: PACT), also known as optoacoustic tomography, is a rapidly emerging imaging modality that holds great promise for a wide range of biomedical imaging applications. Much effort has been devoted to the investigation of imaging physics and the optimization of experimental designs. Meanwhile, a variety of image reconstruction algorithms have been developed for the purpose of computed tomography. Most of these algorithms assume full knowledge of the acoustic pressure function on a measurement surface that either encloses the object or extends to infinity, which poses many difficulties for practical applications. To overcome these limitations, iterative image reconstruction algorithms have been actively investigated. However, little work has been conducted on imaging models that incorporate the characteristics of data acquisition systems. Moreover, when applying to experimental data, most studies simplify the inherent three-dimensional wave propagation as two-dimensional imaging models by introducing heuristic assumptions on the transducer responses and/or the object structures. One important reason is because three-dimensional image reconstruction is computationally burdensome. The inaccurate imaging models severely limit the performance of iterative image reconstruction algorithms in practice. In the dissertation, we propose a framework to construct imaging models that incorporate the characteristics of ultrasonic transducers. Based on the imaging models, we systematically investigate various iterative image reconstruction algorithms, including advanced algorithms that employ total variation-norm regularization. In order to accelerate three-dimensional image reconstruction, we develop parallel implementations on graphic processing units. In addition, we derive a fast Fourier-transform based analytical image reconstruction formula. By use of iterative image reconstruction algorithms based on the proposed imaging models, PACT imaging scanners can have a compact size while maintaining high spatial resolution. The research demonstrates, for the first time, the feasibility and advantages of iterative image reconstruction algorithms in three-dimensional PACT.
Photoacoustic computed tomography (PACT) is an emerging imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the photoacoustically induced initial pressure distribution within tissue. The PACT reconstruction problem corresponds to an inverse source problem in which the initial pressure distribution is recovered from measurements of the radiated pressure wavefield. A major challenge in transcranial PACT brain imaging is compensation for aberrations in the measured data due to the presence of the skull. Ultrasonic waves undergo absorption, scattering and longitudinal-to-shear wave mode conversion as they propagate through the skull. To properly account for these effects, a wave-equation-based inversion method should be employed that can model the heterogeneous elastic properties of the skull. In this dissertation, a forward model based on a finite-difference time-domain discretization of the three-dimensional elastic wave equation is established and a procedure for computing the corresponding adjoint of the forward operator is presented. Massively parallel implementations of these operators employing multiple graphics processing units (GPUs) are also developed. The proposed matched forward-adjoint operator pair is then utilized to develop an optimization-based image reconstruction method for 3D transcranial PACT. The optimization-based image reconstruction method employs the developed numerical framework to compute penalized least squares estimates of the initial pressure distribution. Computer-simulation and experimental studies are conducted to investigate the robustness of the optimization-based reconstruction method to noise, model mismatch and its ability to effectively resolve cortical and superficial brain structures. To properly compensate for the distortions in measured pressure data caused by the presence of the skull, the developed optimization-based image reconstruction methods require knowledge of the spatial distribution of the acoustic parameters of the skull. However, estimating the spatial distribution of the acoustic properties of the skull prior to the PACT experiment remains challenging. Inspired by the observation that information about the distribution of skull acoustic parameters is encoded in PACT measurements, in this dissertation a method to jointly reconstruct the initial pressure distribution and the low-dimensional representation of the spatial distribution of the acoustic properties of the skull from PACT data alone is proposed. The proposed joint reconstruction (JR) algorithm is evaluated through three-dimensional computer-simulation studies that closely mimic transcranial PACT experiments.
Photoacoustic tomography (PAT) is an emerging imaging modality capable of mapping optical absorption in tissues. It is a hybrid technique that combines the high spatial resolution of ultrasound imaging with the high contrast of optical imaging, and has demonstrated much potential in biomedical applications. Conventional PAT systems employ raster scanning to capture a large number of projections, thus improving image reconstruction at the cost of temporal resolution. Arising from the desire for real-time 3D PA imaging, several groups have begun to design PAT systems with staring arrays, where image acquisition is only limited by the repetition rate of the laser. However, there has been little emphasis on staring array design analysis and optimization. We have developed objective figures of merit for PAT system performance and applied these metrics to improve system design. The results suggested that the developed approach could be used to objectively characterize and improve any PAT system design.
The ability to visualize, non-invasively, human internal organs in their true from and shape has intrigued mankind for centuries. While the recent inventions of medical imaging modalities such as computerized tomography and magnetic resonance imaging have revolutionized radiology, the development of three-dimensional (3D) imaging has brought us closer to the age-old quest of non-invasive visualization. The ability to not only visualize but to manipulate and analyze 3D structures from captured multidimensional image data, is vital to a number of diagnostic and therapeutic applications. 3D Imaging in Medicine, Second Edition, unique in its contents, covers both the technical aspects and the actual medical applications of the process in a single source. The value of this technology is obvious. For example, three dimensional imaging allows a radiologist to accurately target the positioning and dosage of chemotherapy as well as to make more accurate diagnoses by showing more pathology; it allows the vascular surgeon to study the flow of blood through clogged arteries; it allows the orthopedist to find all the pieces of a compound fracture; and, it allows oncologists to perform less invasive biopsies. In fact, one of the most important uses of 3D Imaging is in computer-assisted surgery. For example, in cancer surgery, computer images show the surgeon the extent of the tumor so that only the diseased tissue is removed. In short, 3D imaging provides clinicians with information that saves time and money. 3D Imaging in Medicine, Second Edition provides a ready reference on the fundamental science of 3D imaging and its medical applications. The chapters have been written by experts in the field, and the technical aspects are covered in a tutorial fashion, describing the basic principles and algorithms in an easily understandable way. The application areas covered include: surgical planning, neuro-surgery, orthopedics, prosthesis design, brain imaging, analysis of cardio-pulmonary structures, and the assessment of clinical efficacy. The book is designed to provide a quick and systematic understanding of the principles of biomedical visualization to students, scientists and researchers, and to act as a source of information to medical practitioners on a wide variety of clinical applications of 3D imaging.
This book is designed to serve as an up-to-date reference on the use of cone-beam computed tomography for the purpose of 3D imaging of the craniofacial complex. The focus is in particular on the ways in which craniofacial 3D imaging changes how we think about conventional diagnosis and treatment planning and on its clinical applications within orthodontics and oral and maxillofacial surgery. Emphasis is placed on the value of 3D imaging in visualizing the limits of the alveolar bone, the airways, and the temporomandibular joints and the consequences for treatment planning and execution. The book will equip readers with the knowledge required in order to apply and interpret 3D imaging to the benefit of patients. All of the authors have been carefully selected on the basis of their expertise in the field. In describing current thinking on the merits of 3D craniofacial imaging, they draw both on the available scientific literature and on their own translational research findings.
Due to the availability of commercial laboratory systems and the emergence of user facilities at synchrotron radiation sources, studies of microcomputed tomography or microCT have increased exponentially. MicroComputed Technology provides a complete introduction to the technology, describing how to use it effectively and understand its results. The first part of the book focuses on methodology, covering experimental methods, data analysis, and visualization approaches. The second part addresses various microCT applications, including porous solids, microstructural evolution, soft tissue studies, multimode studies, and indirect analyses. The author presents a sufficient amount of fundamental material so that those new to the field can develop a relative understanding of how to design their own microCT studies. One of the first full-length references dedicated to microCT, this book provides an accessible introduction to field, supplemented with application examples and color images.
This is a practical guide to tomographic image reconstruction with projection data, with strong focus on Computed Tomography (CT) and Positron Emission Tomography (PET). Classic methods such as FBP, ART, SIRT, MLEM and OSEM are presented with modern and compact notation, with the main goal of guiding the reader from the comprehension of the mathematical background through a fast-route to real practice and computer implementation of the algorithms. Accompanied by example data sets, real ready-to-run Python toolsets and scripts and an overview the latest research in the field, this guide will be invaluable for graduate students and early-career researchers and scientists in medical physics and biomedical engineering who are beginners in the field of image reconstruction. A top-down guide from theory to practical implementation of PET and CT reconstruction methods, without sacrificing the rigor of mathematical background Accompanied by Python source code snippets, suggested exercises, and supplementary ready-to-run examples for readers to download from the CRC Press website Ideal for those willing to move their first steps on the real practice of image reconstruction, with modern scientific programming language and toolsets Daniele Panetta is a researcher at the Institute of Clinical Physiology of the Italian National Research Council (CNR-IFC) in Pisa. He earned his MSc degree in Physics in 2004 and specialisation diploma in Health Physics in 2008, both at the University of Pisa. From 2005 to 2007, he worked at the Department of Physics "E. Fermi" of the University of Pisa in the field of tomographic image reconstruction for small animal imaging micro-CT instrumentation. His current research at CNR-IFC has as its goal the identification of novel PET/CT imaging biomarkers for cardiovascular and metabolic diseases. In the field micro-CT imaging, his interests cover applications of three-dimensional morphometry of biosamples and scaffolds for regenerative medicine. He acts as reviewer for scientific journals in the field of Medical Imaging: Physics in Medicine and Biology, Medical Physics, Physica Medica, and others. Since 2012, he is adjunct professor in Medical Physics at the University of Pisa. Niccolò Camarlinghi is a researcher at the University of Pisa. He obtained his MSc in Physics in 2007 and his PhD in Applied Physics in 2012. He has been working in the field of Medical Physics since 2008 and his main research fields are medical image analysis and image reconstruction. He is involved in the development of clinical, pre-clinical PET and hadron therapy monitoring scanners. At the time of writing this book he was a lecturer at University of Pisa, teaching courses of life-sciences and medical physics laboratory. He regularly acts as a referee for the following journals: Medical Physics, Physics in Medicine and Biology, Transactions on Medical Imaging, Computers in Biology and Medicine, Physica Medica, EURASIP Journal on Image and Video Processing, Journal of Biomedical and Health Informatics.
This book highlights the use of LEDs in biomedical photoacoustic imaging. In chapters written by key opinion leaders in the field, it covers a broad range of topics, including fundamentals, principles, instrumentation, image reconstruction and data/image processing methods, preclinical and clinical applications of LED-based photoacoustic imaging. Apart from preclinical imaging studies and early clinical pilot studies using LED-based photoacoustics, the book includes a chapter exploring the opportunities and challenges of clinical translation from an industry perspective. Given its scope, the book will appeal to scientists and engineers in academia and industry, as well as medical experts interested in the clinical applications of photoacoustic imaging.
Photoacoustics promises to revolutionize medical imaging and may well make as dramatic a contribution to modern medicine as the discovery of the x-ray itself once did. Combining electromagnetic and ultrasonic waves synergistically, photoacoustics can provide deep speckle-free imaging with high electromagnetic contrast at high ultrasonic resolution and without any health risk. While photoacoustic imaging is probably the fastest growing biomedical imaging technology, this book is the first comprehensive volume in this emerging field covering both the physics and the remarkable noninvasive applications that are changing diagnostic medicine. Bringing together the leading pioneers in this field to write about their own work, Photoacoustic Imaging and Spectroscopy is the first to provide a full account of the latest research and developing applications in the area of biomedical photoacoustics. Photoacoustics can provide functional sensing of physiological parameters such as the oxygen saturation of hemoglobin. It can also provide high-contrast functional imaging of angiogenesis and hypermetabolism in tumors in vivo. Discussing these remarkable noninvasive applications and so much more, this reference is essential reading for all researchers in medical imaging and those clinicians working at the cutting-edge of modern biotechnology to develop diagnostic techniques that can save many lives and just as importantly do no harm.