Download or read book Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms written by Bhabesh Deka and published by Springer. This book was released on 2018-12-29 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review of the recent developments in fast L1-norm regularization-based compressed sensing (CS) magnetic resonance image reconstruction algorithms. Compressed sensing magnetic resonance imaging (CS-MRI) is able to reduce the scan time of MRI considerably as it is possible to reconstruct MR images from only a few measurements in the k-space; far below the requirements of the Nyquist sampling rate. L1-norm-based regularization problems can be solved efficiently using the state-of-the-art convex optimization techniques, which in general outperform the greedy techniques in terms of quality of reconstructions. Recently, fast convex optimization based reconstruction algorithms have been developed which are also able to achieve the benchmarks for the use of CS-MRI in clinical practice. This book enables graduate students, researchers, and medical practitioners working in the field of medical image processing, particularly in MRI to understand the need for the CS in MRI, and thereby how it could revolutionize the soft tissue imaging to benefit healthcare technology without making major changes in the existing scanner hardware. It would be particularly useful for researchers who have just entered into the exciting field of CS-MRI and would like to quickly go through the developments to date without diving into the detailed mathematical analysis. Finally, it also discusses recent trends and future research directions for implementation of CS-MRI in clinical practice, particularly in Bio- and Neuro-informatics applications.
Download or read book Compressed Sensing for Magnetic Resonance Image Reconstruction written by Angshul Majumdar and published by Cambridge University Press. This book was released on 2015-02-26 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expecting the reader to have some basic training in liner algebra and optimization, the book begins with a general discussion on CS techniques and algorithms. It moves on to discussing single channel static MRI, the most common modality in clinical studies. It then takes up multi-channel MRI and the interesting challenges consequently thrown up in signal reconstruction. Off-line and on-line techniques in dynamic MRI reconstruction are visited. Towards the end the book broadens the subject by discussing how CS is being applied to other areas of biomedical signal processing like X-ray, CT and EEG acquisition. The emphasis throughout is on qualitative understanding of the subject rather than on quantitative aspects of mathematical forms. The book is intended for MRI engineers interested in the brass tacks of image formation; medical physicists interested in advanced techniques in image reconstruction; and mathematicians or signal processing engineers.
Download or read book Magnetic Resonance Image Reconstruction written by Mehmet Akcakaya and published by Academic Press. This book was released on 2022-11-04 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Magnetic Resonance Image Reconstruction: Theory, Methods and Applications presents the fundamental concepts of MR image reconstruction, including its formulation as an inverse problem, as well as the most common models and optimization methods for reconstructing MR images. The book discusses approaches for specific applications such as non-Cartesian imaging, under sampled reconstruction, motion correction, dynamic imaging and quantitative MRI. This unique resource is suitable for physicists, engineers, technologists and clinicians with an interest in medical image reconstruction and MRI. - Explains the underlying principles of MRI reconstruction, along with the latest research - Gives example codes for some of the methods presented - Includes updates on the latest developments, including compressed sensing, tensor-based reconstruction and machine learning based reconstruction
Download or read book Algorithms for Sparsity Constrained Optimization written by Sohail Bahmani and published by Springer Science & Business Media. This book was released on 2013-10-07 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a "greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.
Download or read book A Mathematical Introduction to Compressive Sensing written by Simon Foucart and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.
Download or read book Compressed Sensing written by Yonina C. Eldar and published by Cambridge University Press. This book was released on 2012-05-17 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compressed sensing is an exciting, rapidly growing field, attracting considerable attention in electrical engineering, applied mathematics, statistics and computer science. This book provides the first detailed introduction to the subject, highlighting theoretical advances and a range of applications, as well as outlining numerous remaining research challenges. After a thorough review of the basic theory, many cutting-edge techniques are presented, including advanced signal modeling, sub-Nyquist sampling of analog signals, non-asymptotic analysis of random matrices, adaptive sensing, greedy algorithms and use of graphical models. All chapters are written by leading researchers in the field, and consistent style and notation are utilized throughout. Key background information and clear definitions make this an ideal resource for researchers, graduate students and practitioners wanting to join this exciting research area. It can also serve as a supplementary textbook for courses on computer vision, coding theory, signal processing, image processing and algorithms for efficient data processing.
Download or read book Pattern Recognition and Machine Intelligence written by Bhabesh Deka and published by Springer Nature. This book was released on 2019-11-25 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.
Download or read book Current and Future Role of Artificial Intelligence in Cardiac Imaging written by Steffen Erhard Petersen and published by Frontiers Media SA. This book was released on 2020-10-09 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Download or read book Compressed Sensing for Engineers written by Angshul Majumdar and published by CRC Press. This book was released on 2018-12-07 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compressed Sensing (CS) in theory deals with the problem of recovering a sparse signal from an under-determined system of linear equations. The topic is of immense practical significance since all naturally occurring signals can be sparsely represented in some domain. In recent years, CS has helped reduce scan time in Magnetic Resonance Imaging (making scans more feasible for pediatric and geriatric subjects) and has also helped reduce the health hazard in X-Ray Computed CT. This book is a valuable resource suitable for an engineering student in signal processing and requires a basic understanding of signal processing and linear algebra. Covers fundamental concepts of compressed sensing Makes subject matter accessible for engineers of various levels Focuses on algorithms including group-sparsity and row-sparsity, as well as applications to computational imaging, medical imaging, biomedical signal processing, and machine learning Includes MATLAB examples for further development
Download or read book Photoacoustic Tomography PAT written by Xueding Wang and published by MDPI. This book was released on 2021-02-17 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Photoacoustic (or optoacoustic) imaging, including photoacoustic tomography (PAT) and photoacoustic microscopy (PAM), is an emerging imaging modality with great clinical potential. PAI’s deep tissue penetration and fine spatial resolution also hold great promise for visualizing physiology and pathology at the molecular level. PAI combines optical contrast with ultrasonic resolution, and is capable of imaging at depths of up to 7 cm with a real-time scalable spatial resolution of 10 to 500 µm. PAI has demonstrated applications in brain imaging and cancer imaging, such as breast cancer, prostate cancer, ovarian cancer etc. This Special Issue focuses on the novel technological developments and pre-clinical and clinical biomedical applications of PAI. Topics include but are not limited to: brain imaging; cancer imaging; image reconstruction; quantitative imaging; light source and delivery for PAI; photoacoustic detectors; nanoparticles designed for PAI; photoacoustic molecular imaging; photoacoustic spectroscopy.
Download or read book Compressed Sensing with Side Information on the Feasible Region written by Mohammad Rostami and published by Springer. This book was released on 2013-05-15 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses compressive sensing in the presence of side information. Compressive sensing is an emerging technique for efficiently acquiring and reconstructing a signal. Interesting instances of Compressive Sensing (CS) can occur when, apart from sparsity, side information is available about the source signals. The side information can be about the source structure, distribution, etc. Such cases can be viewed as extensions of the classical CS. In these cases we are interested in incorporating the side information to either improve the quality of the source reconstruction or decrease the number of samples required for accurate reconstruction. In this book we assume availability of side information about the feasible region. The main applications investigated are image deblurring for optical imaging, 3D surface reconstruction, and reconstructing spatiotemporally correlated sources. The author shows that the side information can be used to improve the quality of the reconstruction compared to the classic compressive sensing. The book will be of interest to all researchers working on compressive sensing, inverse problems, and image processing.
Download or read book Magnetic Resonance Sensors written by Robert H. Morris and published by MDPI. This book was released on 2018-10-04 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Magnetic Resonance Sensors" that was published in Sensors
Download or read book Computational Modelling of Objects Represented in Images III written by Paolo Di Giamberardino and published by CRC Press. This book was released on 2012-08-24 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III contains all contributions presented at the International Symposium CompIMAGE 2012 - Computational Modelling of Object Presented in Images: Fundamentals, Methods and Applications (Rome, Italy, 5-7 September 2012). The contributions cover the state-of-art and new trends in the fields of: - 3D Vision; - Biometric Recognition; - Computational Bioimaging and Visualization; - Computer Vision in Robotics and Automation; - Data Acquisition, Interpolation, Registration and Compression; - Image Enhancement and Restoring; - Image Processing and Analysis; - Image Segmentation; - Medical Imaging; - Modeling and Simulation; - Motion and Deformation Analysis; - Remote Sensing; - Scientific Visualization Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III addresses different techniques, such as optimization methods, geometry, finite element method, principal component analysis, stochastic methods, neural networks and fuzzy logic. The book is useful to researchers and students with multidisciplinary interests related to Computational Vision, Computational Mechanics, Medicine, Engineering and Architecture.
Download or read book Medical Imaging written by Troy Farncombe and published by CRC Press. This book was released on 2017-12-19 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book has two intentions. First, it assembles the latest research in the field of medical imaging technology in one place. Detailed descriptions of current state-of-the-art medical imaging systems (comprised of x-ray CT, MRI, ultrasound, and nuclear medicine) and data processing techniques are discussed. Information is provided that will give interested engineers and scientists a solid foundation from which to build with additional resources. Secondly, it exposes the reader to myriad applications that medical imaging technology has enabled.
Download or read book Computer Vision ACCV 2014 written by Daniel Cremers and published by Springer. This book was released on 2015-04-15 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five-volume set LNCS 9003--9007 constitutes the thoroughly refereed post-conference proceedings of the 12th Asian Conference on Computer Vision, ACCV 2014, held in Singapore, Singapore, in November 2014. The total of 227 contributions presented in these volumes was carefully reviewed and selected from 814 submissions. The papers are organized in topical sections on recognition; 3D vision; low-level vision and features; segmentation; face and gesture, tracking; stereo, physics, video and events; and poster sessions 1-3.
Download or read book Pattern Recognition and Computer Vision written by Yuxin Peng and published by Springer Nature. This book was released on 2020-10-12 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 12305, 12306, and 12307 constitutes the refereed proceedings of the Third Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2020, held virtually in Nanjing, China, in October 2020. The 158 full papers presented were carefully reviewed and selected from 402 submissions. The papers have been organized in the following topical sections: Part I: Computer Vision and Application, Part II: Pattern Recognition and Application, Part III: Machine Learning.
Download or read book Modern Communications Technology written by Natasa Zivic and published by Walter de Gruyter GmbH & Co KG. This book was released on 2016-08-22 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book explains in a comprehensive way the basic terms of communication engineering, giving a proper amount of the needed mathematical background and explanations of the physical nature of the problems. The theory of communication sciences is explained by using knowledge and examples from real-world applications. The information is presented in a way that is understandable also for those who are not directly involved in communication sciences, but would like to learn more about them.
