Machine Learning in Medical Imaging, Luping Zhou; Li Wang; Qian Wang; Yinghuan Shi

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 124150.00 T
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Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Автор: Wu, Guorong
Название: Machine Learning and Medical Imaging
ISBN: 0128040769 ISBN-13(EAN): 9780128040768
Издательство: Elsevier Science
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Цена: 110030.00 T
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Описание: 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.

Автор: Wang
Название: Machine Learning in Medical Imaging
ISBN: 3319471562 ISBN-13(EAN): 9783319471563
Издательство: Springer
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Цена: 54040.00 T
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Описание: This book constitutes the refereed proceedings of the 7th International Workshop on Machine Learning in Medical Imaging, MLMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging.

Автор: Qian Wang; Yinghuan Shi; Heung-Il Suk; Kenji Suzuk
Название: Machine Learning in Medical Imaging
ISBN: 3319673882 ISBN-13(EAN): 9783319673882
Издательство: Springer
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Цена: 60550.00 T
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Описание: This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging.

Автор: Guorong Wu; Daoqiang Zhang; Luping Zhou
Название: Machine Learning in Medical Imaging
ISBN: 3319105809 ISBN-13(EAN): 9783319105802
Издательство: Springer
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Цена: 52170.00 T
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Описание: 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.

Автор: Kanwal Bhatia; Herve Lombaert
Название: Machine Learning Meets Medical Imaging
ISBN: 3319279289 ISBN-13(EAN): 9783319279282
Издательство: Springer
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Цена: 37270.00 T
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Описание: The papers communicate thespecific needs and nuances of medical imaging to the machine learning communitywhile exposing the medical imaging community to current trends in machinelearning.

Автор: Fei Wang; Dinggang Shen; Pingkun Yan; Kenji Suzuki
Название: Machine Learning in Medical Imaging
ISBN: 3642354270 ISBN-13(EAN): 9783642354274
Издательство: Springer
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Цена: 42860.00 T
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Описание: This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging.

Автор: Guorong Wu; Daoqiang Zhang; Dinggang Shen; Pingkun
Название: Machine Learning in Medical Imaging
ISBN: 3319022660 ISBN-13(EAN): 9783319022666
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013.

Автор: Barber
Название: Bayesian Reasoning and Machine Learning
ISBN: 0521518148 ISBN-13(EAN): 9780521518147
Издательство: Cambridge Academ
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Цена: 73920.00 T
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Описание: This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.

Автор: Bushberg
Название: The Essential Physics of Medical Imaging
ISBN: 0683301187 ISBN-13(EAN): 9780683301182
Издательство: Lippincott Williams & Wilkins
Цена: 126990.00 T
Наличие на складе: Невозможна поставка.
Описание: "Developed from the authors' highly successful annual imaging physics review course, this new Second Edition gives readers a clear, fundamental understanding of the theory and applications of physics in radiology, nuclear medicine, and radiobiology. The Essential Physics of Medical Imaging, Second Edition provides key coverage of the clinical implications of technical principles--making this book great for board review.

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 57970.00 T
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Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Автор: Bekkerman
Название: Scaling up Machine Learning
ISBN: 0521192242 ISBN-13(EAN): 9780521192248
Издательство: Cambridge Academ
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Цена: 98210.00 T
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Описание: In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a variety of machine learning methods developed specifically for parallel or distributed systems, covering algorithms, platforms and applications.