Development of Transport-theory-based Reconstruction Algorithms for Optical Tomographic Imaging of Small-tissue Volumes PDF Download
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Author: Xuejun Gu
Publisher:
ISBN:
Category :
Languages : en
Pages : 394
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Author: Xuejun Gu
Publisher:
ISBN:
Category :
Languages : en
Pages : 394
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Author: John C. Rasmussen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Herein we present the development of a fluorescence-enhanced, frequency-domain radiative transport reconstruction system designed for small animal optical tomography. The system includes a time-dependent data acquisition instrument, a radiative transport based forward model for prediction of time-dependent propagation of photons in small, non-diffuse volumes, and an algorithm which utilizes the forward model to reconstruct fluorescent yields from air/tissue boundary measurements. The major components of the instrumentation include a charge coupled device camera, an image intensifier, signal generators, and an optical switch. Time-dependent data were obtained in the frequency-domain using homodyne techniques on phantoms with 0.2% to 3% intralipid solutions. Through collaboration with Transpire, Inc., a fluorescence-enhanced, frequency-domain, radiative transport equation (RTE) solver was developed. This solver incorporates the discrete ordinates, source iteration with diffusion synthetic acceleration, and linear discontinuous finite element differencing schemes, to predict accurately the fluence of excitation and emission photons in diffuse and transport limited systems. Additional techniques such as the first scattered distributed source method and integral transport theory are used to model the numerical apertures of fiber optic sources and detectors. The accuracy of the RTE solver was validated against diffusion and Monte Carlo predictions and experimental data. The comparisons were favorable in both the diffusion and transport limits, with average errors of the RTE predictions, as compared to experimental data, typically being less than 8% in amplitude and 7% in phase. These average errors are similar to those of the Monte Carlo and diffusion predictions. Synthetic data from a virtual mouse were used to demonstrate the feasibility of using the RTE solver for reconstructing fluorescent heterogeneities in small, non-diffuse volumes. The current version of the RTE solver limits the reconstruction to one iteration and the reconstruction of marginally diffuse, frequency-domain experimental data using RTE was not successful. Multiple iterations using a diffusion solver successfully reconstructed the fluorescent heterogeneities, indicating that, when available, multiple iterations of the RTE based solver should also reconstruct the heterogeneities.
Author: Daniele Panetta
Publisher: CRC Press
ISBN: 100017588X
Category : Medical
Languages : en
Pages : 97
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Book Description
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.
Author: Yulia Levakhina
Publisher: Springer
ISBN: 3658056975
Category : Computers
Languages : en
Pages : 205
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Book Description
Yulia Levakhina gives an introduction to the major challenges of image reconstruction in Digital Tomosynthesis (DT), particularly to the connection of the reconstruction problem with the incompleteness of the DT dataset. The author discusses the factors which cause the formation of limited angle artifacts and proposes how to account for them in order to improve image quality and axial resolution of modern DT. The addressed methods include a weighted non-linear back projection scheme for algebraic reconstruction and novel dual-axis acquisition geometry. All discussed algorithms and methods are supplemented by detailed illustrations, hints for practical implementation, pseudo-code, simulation results and real patient case examples.
Author: Gabor T. Herman
Publisher: Springer Science & Business Media
ISBN: 1846287235
Category : Computers
Languages : en
Pages : 302
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Book Description
This revised and updated second edition – now with two new chapters - is the only book to give a comprehensive overview of computer algorithms for image reconstruction. It covers the fundamentals of computerized tomography, including all the computational and mathematical procedures underlying data collection, image reconstruction and image display. Among the new topics covered are: spiral CT, fully 3D positron emission tomography, the linogram mode of backprojection, and state of the art 3D imaging results. It also includes two new chapters on comparative statistical evaluation of the 2D reconstruction algorithms and alternative approaches to image reconstruction.
Author: Guillaume Bal
Publisher: American Mathematical Soc.
ISBN: 0821853015
Category : Mathematics
Languages : en
Pages : 194
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Book Description
This volume contains research and review articles written by participants of two related international workshops ``Mathematical Methods in Emerging Modalities of Medical Imaging'' (October 2009) and ``Inverse Transport Theory and Tomography'' (May 2010), which were held at the Banff International Research Station in Banff, Canada. These workshops brought together mathematicians, physicists, engineers, and medical researchers working at the cutting edge of medical imaging research and addressed the demanding mathematical problems arising in this area. The articles, written by leading experts, address important analytic, numerical, and physical issues of the newly developing imaging modalities (e.g., photoacoustics, current impedance imaging, hybrid imaging techniques, elasticity imaging), as well as the recent progress in resolving outstanding problems of more traditional modalities, such as SPECT, ultrasound imaging, and inverse transport theory. Related topics of invisibility cloaking are also addressed.
Author: Gabor T. Herman
Publisher:
ISBN:
Category : Medical
Languages : en
Pages : 352
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Book Description
Image reconstruction from projections. Probability and random variables. An overview of the process of CT. Physical problems associated with data collection in CT. Computer simulation of data collection in CT. Data collection and reconstruction of the head phantom under various assumptions. Basic concepts of reconstruction algorithms. Backprojection. Convolution method for parallel beams. Other transform methods for parallel beams. Convolution methods for divergent beams. The algebraic reconstruction techniques. Quadratic optimization methods. Noniterative series expansion methods. Truly three-dimensional reconstruction. Three-dimensional display of organs. Mathematical background.
Author: David A. Boas
Publisher: CRC Press
ISBN: 1420090372
Category : Medical
Languages : en
Pages : 816
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Biomedical optics holds tremendous promise to deliver effective, safe, non- or minimally invasive diagnostics and targeted, customizable therapeutics. Handbook of Biomedical Optics provides an in-depth treatment of the field, including coverage of applications for biomedical research, diagnosis, and therapy. It introduces the theory and fundamental
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 244
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Optical tomography, specically, diffuse optical tomography (DOT) and fluorescent molecular tomography (FMT) are promising functional imaging modalities with a high sensitivity and specicity. However, the inverse problem of DOT and FMT are ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution for deep target imaging. It is well known that DOT and FMT image quality can be improved substantially by applying the structural guidance in the reconstruction algorithm. In this dissertation, First, I conducted a feasibility study of computed tomography (CT) guided DOT system for breast cancer imaging. I built a noncontact projection style prototype DOT which consists of a laser at the wavelength of 650 nm and an electron multiplying charge coupled device (EMCCD) camera. We have validated the CT-guided DOT reconstruction algorithms with numerical simulations and phantom experiments, in which different imaging setup parameters, such as projection number of measurements and width of measurement patch, have been investigated. Secondly, inspired by the kernel methods in machine learning, I introduced a kernel-based image reconstruction algorithm into anatomical image-guided DOT. Compared with conventional Laplacian approaches that include structural priors by regularization matrix, the developed method applied in this research incorporates a kernel matrix with the projection model into the objective function and does not require image segmentation. The optical absorption coefficient at each nite element node is represented as a function of a set of features obtained fromanatomical images such as computed tomography (CT) images. The proposed kernel method is validated with numerical simulations and agar phantom experiments. The proposed method utilized a CT volume data set without segmentation from a clinical breast CT system in the DOT. Lastly, I implemented kernel-based anatomical guidance into the FMT image reconstruction. In FMT, the fluorophore concentration at each node is dened as a function of a set of feature vectors, which is directly extracted from the voxel intensities of the corresponding anatomical 3D images. This research studied the effects of voxel size and a number of nearest neighbors in the kernel method on the quality of reconstructed FMT images. The results indicate that the spatial resolution and the accuracy of the reconstructed FMT images have been improved substantially after applying the anatomical guidance with the proposed kernel method. The proposed method utilized magnetic resonance imaging (MRI) rat brain image in FMT simulation, which further proved that we do not need to segment the anatomical image for the kernel method. The proposed kernel method was found to be robust to the false positive guidance in the anatomical image. As future work, the DOT prototype system will be integrated with a dedicated CT system, and clinical trials will be conducted using kernel-based image reconstruction algorithm.
Author: Jicun Hu
Publisher:
ISBN:
Category : Diagnostic imaging
Languages : en
Pages : 322
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