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Post Reconstruction Image Denoising And Artefact Removal For Low Count Positron Emission Tomography
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Book Synopsis Post-reconstruction Image Denoising and Artefact Removal for Low Count Positron Emission Tomography by : Casper da Costa-Luis
Download or read book Post-reconstruction Image Denoising and Artefact Removal for Low Count Positron Emission Tomography written by Casper da Costa-Luis and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis 3D Image Reconstruction for CT and PET by : Daniele Panetta
Download or read book 3D Image Reconstruction for CT and PET written by Daniele Panetta and published by CRC Press. This book was released on 2020-10-11 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Correction Techniques in Emission Tomography by : Mohammad Dawood
Download or read book Correction Techniques in Emission Tomography written by Mohammad Dawood and published by CRC Press. This book was released on 2012-04-27 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by an interdisciplinary team of medical doctors, computer scientists, physicists, engineers, and mathematicians, Correction Techniques in Emission Tomography presents various correction methods used in emission tomography to generate and enhance images. It discusses the techniques from a computer science, mathematics, and physics viewpoint.
Book Synopsis Novel Denoising Methods for Dynamic Positron Emission Tomography by :
Download or read book Novel Denoising Methods for Dynamic Positron Emission Tomography written by and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Positron emission tomography (PET) provides inherently quantitative information about physiological and molecular processes, endowing it with great clinical and research potential. This is particularly true of dynamic PET imaging. Unfortunately, PET, and especially dynamic PET, suffers from unfavorable noise properties, limiting it diagnostically and quantitatively. Denoising methods that improve image quality and thus increase diagnostic accuracy and improve estimates of quantitative parameters could be of great benefit, particularly if they are simple, accurate, and easily implemented on a wide range of PET tracer studies. The aim of this thesis is to develop and evaluate two novel denoising methods for dynamic PET imaging: HighlY constrained back-Projection-Local Reconstruction (HYPR-LR), which has recently been applied to dynamic PET data with promising results, and spatio-temporal expectation maximization (STEM) filtering, a newly developed 4-dimensional iterative filtering process. An implementation of HYPR-LR is presented that provides the maximum amount of noise reduction that is possible without introducing any significant bias. This is accomplished using multiple time-dependent temporally summed composite images that account for the kinetics of the tracer being studied. The potential of HYPR-LR to improve dynamic PET imaging is demonstrated using phantom, simulated, and human data, with a focus on quantitative parametric images. The newly proposed STEM filtering combines two well established image processing techniques: 4-dimensional Gaussian smoothing followed by EM deconvolution. In principle, this approach should provide substantial reductions in noise while introducing little bias. STEM filtering is also evaluated using phantom, simulated, and human data, with a focus on parametric images. The potential of HYPR-LR and STEM filtering to improve PET imaging of [I-124] labeled agents is also studied. [I-124] could be a valuable radionuclide for PET imaging, but its use is often limited by noise because of dosimetry concerns and relatively few decays by positron emission. Finally, the impact of a more traditional means of controlling image noise at the cost of bias, varying the number of iterations performed during EM reconstruction, on the diagnosis of temporal lobe epilepsy is studied. This also serves as an illustration of how HYPR-LR and STEM filtering might be evaluated in a clinical context.
Book Synopsis Medical Image Reconstruction by : Gengsheng Zeng
Download or read book Medical Image Reconstruction written by Gengsheng Zeng and published by Springer Science & Business Media. This book was released on 2010-12-28 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Medical Image Reconstruction: A Conceptual Tutorial" introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l0-minimization are also included. This book is written for engineers and researchers in the field of biomedical engineering specializing in medical imaging and image processing with image reconstruction. Gengsheng Lawrence Zeng is an expert in the development of medical image reconstruction algorithms and is a professor at the Department of Radiology, University of Utah, Salt Lake City, Utah, USA.
Book Synopsis Deep Learning in Medical Image Analysis by : Gobert Lee
Download or read book Deep Learning in Medical Image Analysis written by Gobert Lee and published by Springer Nature. This book was released on 2020-02-06 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
Book Synopsis The Essential Guide to Image Processing by : Alan C. Bovik
Download or read book The Essential Guide to Image Processing written by Alan C. Bovik and published by Academic Press. This book was released on 2009-07-08 with total page 877 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete introduction to the basic and intermediate concepts of image processing from the leading people in the field Up-to-date content, including statistical modeling of natural, anistropic diffusion, image quality and the latest developments in JPEG 2000 This comprehensive and state-of-the art approach to image processing gives engineers and students a thorough introduction, and includes full coverage of key applications: image watermarking, fingerprint recognition, face recognition and iris recognition and medical imaging. "This book combines basic image processing techniques with some of the most advanced procedures. Introductory chapters dedicated to general principles are presented alongside detailed application-orientated ones. As a result it is suitably adapted for different classes of readers, ranging from Master to PhD students and beyond." – Prof. Jean-Philippe Thiran, EPFL, Lausanne, Switzerland "Al Bovik’s compendium proceeds systematically from fundamentals to today’s research frontiers. Professor Bovik, himself a highly respected leader in the field, has invited an all-star team of contributors. Students, researchers, and practitioners of image processing alike should benefit from the Essential Guide." – Prof. Bernd Girod, Stanford University, USA "This book is informative, easy to read with plenty of examples, and allows great flexibility in tailoring a course on image processing or analysis." – Prof. Pamela Cosman, University of California, San Diego, USA A complete and modern introduction to the basic and intermediate concepts of image processing – edited and written by the leading people in the field An essential reference for all types of engineers working on image processing applications Up-to-date content, including statistical modelling of natural, anisotropic diffusion, image quality and the latest developments in JPEG 2000
Book Synopsis Basic Sciences of Nuclear Medicine by : Magdy M. Khalil
Download or read book Basic Sciences of Nuclear Medicine written by Magdy M. Khalil and published by Springer Nature. This book was released on 2021-05-26 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive and detailed information on the scientific bases of nuclear medicine, addressing a wide variety of topics and explaining the concepts that underlie many of the investigations and procedures performed in the field. The book is divided into six sections that cover the physics and chemistry of nuclear medicine besides associated quality assurance/quality control procedures; dosimetry and radiation biology; SPECT and PET imaging instrumentation plus CT imaging technology in hybrid modalities; data analysis including image processing, reconstruction, radiomics, image degrading correction techniques, along with image quantitation and kinetic modeling. Within these sections, particular attention is paid to recent developments and the advances in knowledge that have taken place since release of the first edition in 2011. Several entirely new chapters have been included and the remaining chapters, thoroughly updated. Innovations in the ever-expanding field of nuclear medicine are predominantly due to integration of the basic sciences with complex technological advances. This excellently illustrated book on the subject will be of interest to not only nuclear medicine physicists and physicians but also clinical scientists, radiologists, radiopharmacists, medical students and technologists.
Book Synopsis Machine Learning for Medical Image Reconstruction by : Florian Knoll
Download or read book Machine Learning for Medical Image Reconstruction written by Florian Knoll and published by Springer Nature. This book was released on 2019-10-24 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 24 full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography; and deep learning for general image reconstruction.
Book Synopsis Clinical PET/MRI by : Onofrio Antonio Catalano
Download or read book Clinical PET/MRI written by Onofrio Antonio Catalano and published by Academic Press. This book was released on 2022-09-07 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical PET/MR presents the state-of-the-art of PET/MR, guiding the reader from how to scan patients, how to read and report the studies, and how keep an eye on what is clinically relevant for a patient's care. Each chapter starts with the clinical scenario and then moves to pertinent imaging, addressing the need of a clinical PET/MR book written by world experts in both clinical and imaging fields. It discusses the clinical application of PET/MR in diverse subspecialties such as head and neck, neurology, cardiovascular, pediatrics, chest, bone, hematology, breast, hepatobiliary pancreatic, genitourinary, gynecology, and gastrointestinal tract. This book is a valuable resource for radiologists, oncologists and members of the biomedical field who need to learn more about clinical applications of PET/MR. - Presents a description of robust acquisition protocols to teach readers how to scan PET/MR patients, from tracers to sequences - Provides a clinical background section in each chapter to help readers focus on the real clinical issues that need to be addressed in the medical report - Written by world authorities in the field in a didactic manner to describe the real status of imaging
Book Synopsis Medical Imaging Systems by : Andreas Maier
Download or read book Medical Imaging Systems written by Andreas Maier and published by Springer. This book was released on 2018-08-02 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.
Book Synopsis Introduction to Machine Learning by : Ethem Alpaydin
Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Book Synopsis Fundamentals of Computerized Tomography by : Gabor T. Herman
Download or read book Fundamentals of Computerized Tomography written by Gabor T. Herman and published by Springer Science & Business Media. This book was released on 2009-07-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Theory and Practice of 3D PET by : B. Bendriem
Download or read book The Theory and Practice of 3D PET written by B. Bendriem and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of 3D methodology has recently been receiving increasing attention at many PET centres, and this monograph is an attempt to provide a state-of-the-art review of this methodology, covering 3D reconstruction methods, quantitative procedures, current tomography performance, and clinical and research applications. No such review has been available until now to assist PET researchers in understanding and implementing 3D methodology, and in evaluating the performance of the available imaging technology. In all the chapters, the subject matter is treated in sufficient depth to appeal equally to the physicist or engineer who wishes to establish the methodology, and to PET investigators with experience in 2D PET who wish to familiarize themselves with the concepts and advantages of 3D, and to be made aware of the pitfalls.
Book Synopsis Machine Learning for Tomographic Imaging by : Ge Wang
Download or read book Machine Learning for Tomographic Imaging written by Ge Wang and published by Programme: Iop Expanding Physi. This book was released on 2019-12-30 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning represents a paradigm shift in tomographic imaging, and image reconstruction is a new frontier of machine learning. This book will meet the needs of those who want to catch the wave of smart imaging. The book targets graduate students and researchers in the imaging community. Open network software, working datasets, and multimedia will be included. The first of its kind in the emerging field of deep reconstruction and deep imaging, Machine Learning for Tomographic Imaging presents the most essential elements, latest progresses and an in-depth perspective on this important topic.
Book Synopsis Multiscale Multimodal Medical Imaging by : Quanzheng Li
Download or read book Multiscale Multimodal Medical Imaging written by Quanzheng Li and published by Springer Nature. This book was released on 2019-12-19 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019. The 13 papers presented were carefully reviewed and selected from 18 submissions. The MMMI workshop aims to advance the state of the art in multi-scale multi-modal medical imaging, including algorithm development, implementation of methodology, and experimental studies. The papers focus on medical image analysis and machine learning, especially on machine learning methods for data fusion and multi-score learning.
Book Synopsis Image Mosaicing and Super-resolution by : David Capel
Download or read book Image Mosaicing and Super-resolution written by David Capel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates sets of images consisting of many overlapping viewsofa scene, and how the information contained within them may be combined to produce single images of superior quality. The generic name for such techniques is frame fusion. Using frame fusion, it is possible to extend the fieldof view beyond that ofany single image, to reduce noise, to restore high-frequency content, and even to increase spatial resolution and dynamic range. The aim in this book is to develop efficient, robust and automated frame fusion algorithms which may be applied to real image sequences. An essential step required to enable frame fusion is image registration: computing the point-to-point mapping between images in their overlapping region. This sub problem is considered in detail, and a robust and efficient solution is proposed and its accuracy evaluated. Two forms of frame fusion are then considered: image mosaic ing and super-resolution. Image mosaicing is the alignment of multiple images into a large composition which represents part of a 3D scene. Super-resolution is a more sophisticated technique which aims to restore poor-quality video sequences by mod elling and removing the degradations inherent in the imaging process, such as noise, blur and spatial-sampling. A key element in this book is the assumption of a completely uncalibrated cam era. No prior knowledge of the camera parameters, its motion, optics or photometric characteristics is assumed. The power of the methods is illustrated with many real image sequence examples.
