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Medical Image Segmentation Using Level Sets And Dictionary Learning
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Book Synopsis Medical Image Segmentation Using Level Sets and Dictionary Learning by : Saif Dawood Salman Al-Shaikhli
Download or read book Medical Image Segmentation Using Level Sets and Dictionary Learning written by Saif Dawood Salman Al-Shaikhli and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Biomedical Image Segmentation by : Ayman El-Baz
Download or read book Biomedical Image Segmentation written by Ayman El-Baz and published by CRC Press. This book was released on 2016-11-17 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.
Book Synopsis Level Set Method in Medical Imaging Segmentation by : Ayman El-Baz
Download or read book Level Set Method in Medical Imaging Segmentation written by Ayman El-Baz and published by CRC Press. This book was released on 2019-06-26 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging analysis and segmentation, the function assigns a label to each pixel or voxel and optimality is defined based on desired imaging properties. This often includes a detection step to extract specific objects via segmentation. This allows for the segmentation and analysis problem to be formulated and solved in a principled way based on well-established mathematical theories. Level set method is a great tool for modeling time varying medical images and enhancement of numerical computations.
Book Synopsis Machine Learning in Medical Imaging by : Guorong Wu
Download or read book Machine Learning in Medical Imaging written by Guorong Wu and published by Springer. This book was released on 2014-09-05 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Medical Imaging, MLMI 2014, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, in Cambridge, MA, USA, in September 2014. The 40 contributions included in this volume were carefully reviewed and selected from 70 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
Book Synopsis Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013 by : Kensaku Mori
Download or read book Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013 written by Kensaku Mori and published by Springer. This book was released on 2013-09-20 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 86 papers included in the second volume have been organized in the following topical sections: registration and atlas construction; microscopy, histology, and computer-aided diagnosis; motion modeling and compensation; segmentation; machine learning, statistical modeling, and atlases; computer-aided diagnosis and imaging biomarkers; physiological modeling, simulation, and planning; microscope, optical imaging, and histology; cardiology; vasculatures and tubular structures; brain segmentation and atlases; and functional MRI and neuroscience applications.
Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou
Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-11 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: - Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects - Methods and theories for medical image recognition, segmentation and parsing of multiple objects - Efficient and effective machine learning solutions based on big datasets - Selected applications of medical image parsing using proven algorithms - Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects - Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets - Includes algorithms for recognizing and parsing of known anatomies for practical applications
Book Synopsis Radiomics and Radiogenomics by : Ruijiang Li
Download or read book Radiomics and Radiogenomics written by Ruijiang Li and published by CRC Press. This book was released on 2019-07-09 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radiomics and Radiogenomics: Technical Basis and Clinical Applications provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical bases, and clinical applications with a focus on oncology. The book’s expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and evaluation of therapy response. This book is intended for audiences including imaging scientists, medical physicists, as well as medical professionals and specialists such as diagnostic radiologists, radiation oncologists, and medical oncologists. Features Provides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics Shows how they are improving diagnostic and prognostic decisions with greater efficacy Discusses the image informatics, quantitative imaging, feature extraction, predictive modeling, software tools, and other key areas Covers applications in oncology and beyond, covering all major disease sites in separate chapters Includes an introduction to basic principles and discussion of emerging research directions with a roadmap to clinical translation
Book Synopsis Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 by : Maxime Descoteaux
Download or read book Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 written by Maxime Descoteaux and published by Springer. This book was released on 2017-09-03 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.
Book Synopsis Medical Image Understanding and Analysis by : Bartłomiej W. Papież
Download or read book Medical Image Understanding and Analysis written by Bartłomiej W. Papież and published by Springer Nature. This book was released on 2020-07-08 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 24th Conference on Medical Image Understanding and Analysis, MIUA 2020, held in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 29 full papers and 5 short papers presented were carefully reviewed and selected from 70 submissions. They were organized according to following topical sections: image segmentation; image registration, reconstruction and enhancement; radiomics, predictive models, and quantitative imaging biomarkers; ocular imaging analysis; biomedical simulation and modelling.
Book Synopsis Neural Information Processing by : Derong Liu
Download or read book Neural Information Processing written by Derong Liu and published by Springer. This book was released on 2017-11-07 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.
Book Synopsis Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging by : Bjoern Menze
Download or read book Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging written by Bjoern Menze and published by Springer. This book was released on 2013-03-14 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed workshop proceedings of the Second International Workshop on Medical Computer Vision, MCV 2012, held in Nice, France, October 2012 in conjunction with the 15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012. The 24 papers have been selected out of 42 submissions. At MCV 2012, 12 papers were presented as a poster and 12 as a poster together with a plenary talk. The book also features four selected papers which were presented at the previous CVPR Medical Computer Vision workshop held in conjunction with the International Conference on Computer Vision and Pattern Recognition on June 21 2012 in Providence, Rhode Island, USA. The papers explore the use of modern computer vision technology in tasks such as automatic segmentation and registration, localization of anatomical features and detection of anomalies, as well as 3D reconstruction and biophysical model personalization.
Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou
Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2017-01-18 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache
Book Synopsis Biomedical Information Technology by : David Dagan Feng
Download or read book Biomedical Information Technology written by David Dagan Feng and published by Academic Press. This book was released on 2019-10-22 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modeling, processing, registration, visualization, communication and large-scale biological computing. - Presents the world's most recognized authorities who give their "best practices" - Provides professionals with the most up-to-date and mission critical tools to evaluate the latest advances in the field - Gives new staff the technological fundamentals and updates experienced professionals with the latest practical integrated clinical applications
Book Synopsis Image Processing for Automated Diagnosis of Cardiac Diseases by : Kalpana Chauhan
Download or read book Image Processing for Automated Diagnosis of Cardiac Diseases written by Kalpana Chauhan and published by Academic Press. This book was released on 2021-07-13 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image Processing for Automated Diagnosis of Cardiac Diseases highlights current and emerging technologies for the automated diagnosis of cardiac diseases. It presents concepts and practical algorithms, including techniques for the automated diagnosis of organs in motion using image processing. This book is suitable for biomedical engineering researchers, engineers and scientists in research and development, and clinicians who want to learn more about and develop advanced concepts in image processing to overcome the challenges of automated diagnosis of heart disease. - Includes advanced techniques to improve diagnostic methods for various cardiac diseases - Uses methods to improve the existing diagnostic features of echocardiographic machines - Develops new diagnostic features for echocardiographic machines
Book Synopsis Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 by : Nassir Navab
Download or read book Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 written by Nassir Navab and published by Springer. This book was released on 2015-09-28 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, held in Munich, Germany, in October 2015. Based on rigorous peer reviews, the program committee carefully selected 263 revised papers from 810 submissions for presentation in three volumes. The papers have been organized in the following topical sections: quantitative image analysis I: segmentation and measurement; computer-aided diagnosis: machine learning; computer-aided diagnosis: automation; quantitative image analysis II: classification, detection, features, and morphology; advanced MRI: diffusion, fMRI, DCE; quantitative image analysis III: motion, deformation, development and degeneration; quantitative image analysis IV: microscopy, fluorescence and histological imagery; registration: method and advanced applications; reconstruction, image formation, advanced acquisition - computational imaging; modelling and simulation for diagnosis and interventional planning; computer-assisted and image-guided interventions.
Book Synopsis Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012 by : Nicholas Ayache
Download or read book Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012 written by Nicholas Ayache and published by Springer Science & Business Media. This book was released on 2012-09-22 with total page 807 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The first volume includes 91 papers organized in topical sections on abdominal imaging, computer-assisted interventions and robotics; computer-aided diagnosis and planning; image reconstruction and enhancement; analysis of microscopic and optical images; computer-assisted interventions and robotics; image segmentation; cardiovascular imaging; and brain imaging: structure, function and disease evolution.
Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Image Computing by : Le Lu
Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
