Medical Image Computing And Computer Assisted Intervention Miccai 2014
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Handbook Of Medical Image Computing And Computer Assisted Intervention
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2019-10-18
Handbook Of Medical Image Computing And Computer Assisted Intervention written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Computers categories.
Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. - Presents the key research challenges in medical image computing and computer-assisted intervention - Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society - Contains state-of-the-art technical approaches to key challenges - Demonstrates proven algorithms for a whole range of essential medical imaging applications - Includes source codes for use in a plug-and-play manner - Embraces future directions in the fields of medical image computing and computer-assisted intervention
Medical Image Computing And Computer Assisted Intervention Miccai 2014
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Author : Polina Golland
language : en
Publisher: Springer
Release Date : 2014-08-31
Medical Image Computing And Computer Assisted Intervention Miccai 2014 written by Polina Golland and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-31 with Computers categories.
The three-volume set LNCS 8673, 8674, and 8675 constitutes the refereed proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, held in Boston, MA, USA, in September 2014. Based on rigorous peer reviews, the program committee carefully selected 253 revised papers from 862 submissions for presentation in three volumes. The 100 papers included in the first volume have been organized in the following topical sections: microstructure imaging; image reconstruction and enhancement; registration; segmentation; intervention planning and guidance; oncology; and optical imaging.
Medical Image Computing And Computer Assisted Intervention Miccai 2014
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Author : Polina Golland
language : en
Publisher: Springer
Release Date : 2014-08-31
Medical Image Computing And Computer Assisted Intervention Miccai 2014 written by Polina Golland and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-31 with Computers categories.
The three-volume set LNCS 8673, 8674, and 8675 constitutes the refereed proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, held in Boston, MA, USA, in September 2014. Based on rigorous peer reviews, the program committee carefully selected 253 revised papers from 862 submissions for presentation in three volumes. The 53 papers included in the third volume have been organized in the following topical sections: shape and population analysis; brain; diffusion MRI; and machine learning.
Medical Image Computing And Computer Assisted Intervention Miccai 2014
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Author : Polina Golland
language : en
Publisher: Springer
Release Date : 2014-08-31
Medical Image Computing And Computer Assisted Intervention Miccai 2014 written by Polina Golland and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-31 with Computers categories.
The three-volume set LNCS 8673, 8674, and 8675 constitutes the refereed proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, held in Boston, MA, USA, in September 2014. Based on rigorous peer reviews, the program committee carefully selected 253 revised papers from 862 submissions for presentation in three volumes. The 100 papers included in the second volume have been organized in the following topical sections: biophysical modeling and simulation; atlas-based transfer of boundary conditions for biomechanical simulation; temporal and motion modeling; computer-aided diagnosis; pediatric imaging; endoscopy; ultrasound imaging; machine learning; cardiovascular imaging; intervention planning and guidance; and brain.
Deep Learning And Convolutional Neural Networks For Medical Image Computing
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Author : Le Lu
language : en
Publisher: Springer
Release Date : 2017-07-12
Deep Learning And Convolutional Neural Networks For Medical Image Computing written by Le Lu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with Computers categories.
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.
Machine Learning And Medical Imaging
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Author : Guorong Wu
language : en
Publisher: Academic Press
Release Date : 2016-08-11
Machine Learning And Medical Imaging written by Guorong Wu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-11 with Computers categories.
Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. - Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems - Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics - Features self-contained chapters with a thorough literature review - Assesses the development of future machine learning techniques and the further application of existing techniques
Medical Image Understanding And Analysis
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Author : Moi Hoon Yap
language : en
Publisher: Springer Nature
Release Date : 2024-07-23
Medical Image Understanding And Analysis written by Moi Hoon Yap and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-23 with Computers categories.
This two-volume set LNCS 14859-14860 constitutes the proceedings of the 28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024, held in Manchester, UK, during July 24–26, 2024. The 59 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: Part I : Advancement in Brain Imaging; Medical Images and Computational Models; and Digital Pathology, Histology and Microscopic Imaging. Part II : Dental and Bone Imaging; Enhancing Low-Quality Medical Images; Domain Adaptation and Generalisation; and Dermatology, Cardiac Imaging and Other Medical Imaging.
Biomedical Imaging
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Author : Ankur Gogoi
language : en
Publisher: Springer Nature
Release Date : 2024-09-26
Biomedical Imaging written by Ankur Gogoi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-26 with Science categories.
This book presents the rapidly developing field of artificial intelligence and machine learning and its application in biomedical imaging. As is known, starting from the diagnosis of fractures by using X-rays to understanding the complex structure and function of the brain, biomedical imaging has contributed immensely toward the development of precision diagnosis and treatment strategies for numerous diseases. While continuous evolution in imaging technologies have enabled the acquisition of images having resolution and contrast far better than ever, it significantly increased the volume of data associated with each image scan—making it increasingly difficult for experts to analyze and interpret. In this context, the application of artificial intelligence (AI) and machine learning (ML) tools has become one of the most exciting frontlines of contemporary research in biomedical imaging due to their capability to extract minute traces of various disease signatures from large and complicated datasets and providing clear insight into the potential abnormalities with excellent accuracy, sensitivity, and specificity. The hallmark of this book will be the contributions from international leaders on different AI-aided advanced biomedical imaging modalities and techniques. Included will be comprehensive description of several of the technology-driven spectacular advances made over the past few years that have allowed early detection and delineation of abnormalities with sub-pixel image segmentation and classification. Starting from the fundamentals of biomedical image processing, the book presents a streamlined and focused coverage of the core principles, theoretical and experimental approaches, and state-of-the-art applications of most of the currently used biomedical imaging techniques powered by AI.
Brain Mapping
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Author :
language : en
Publisher: Academic Press
Release Date : 2015-02-14
Brain Mapping written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-14 with Science categories.
Brain Mapping: A Comprehensive Reference, Three Volume Set offers foundational information for students and researchers across neuroscience. With over 300 articles and a media rich environment, this resource provides exhaustive coverage of the methods and systems involved in brain mapping, fully links the data to disease (presenting side by side maps of healthy and diseased brains for direct comparisons), and offers data sets and fully annotated color images. Each entry is built on a layered approach of the content – basic information for those new to the area and more detailed material for experienced readers. Edited and authored by the leading experts in the field, this work offers the most reputable, easily searchable content with cross referencing across articles, a one-stop reference for students, researchers and teaching faculty. Broad overview of neuroimaging concepts with applications across the neurosciences and biomedical research Fully annotated color images and videos for best comprehension of concepts Layered content for readers of different levels of expertise Easily searchable entries for quick access of reputable information Live reference links to ScienceDirect, Scopus and PubMed
Medical Image Recognition Segmentation And Parsing
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2015-12-11
Medical Image Recognition Segmentation And Parsing written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-11 with Computers categories.
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