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Marginal Space Learning for Medical Image Analysis, Yefeng Zheng; Dorin Comaniciu


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Автор: Yefeng Zheng; Dorin Comaniciu
Название:  Marginal Space Learning for Medical Image Analysis
ISBN: 9781493955756
Издательство: Springer
Классификация:


ISBN-10: 1493955756
Обложка/Формат: Paperback
Страницы: 268
Вес: 0.41 кг.
Дата издания: 03.09.2016
Язык: English
Размер: 234 x 156 x 16
Основная тема: Computer Science
Подзаголовок: Efficient Detection and Segmentation of Anatomical Structures
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.

Natural User Interfaces in Medical Image Analysis

Автор: Marek R. Ogiela; Tomasz Hachaj
Название: Natural User Interfaces in Medical Image Analysis
ISBN: 3319077996 ISBN-13(EAN): 9783319077994
Издательство: Springer
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Цена: 88500.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This unique text/reference highlights a selection of practical applications of advanced image analysis methods for medical images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis.

Marginal Space Learning for Medical Image Analysis

Автор: Zheng
Название: Marginal Space Learning for Medical Image Analysis
ISBN: 1493905996 ISBN-13(EAN): 9781493905997
Издательство: Springer
Рейтинг:
Цена: 74530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Автор: M. Jorge Cardoso; Tal Arbel; Gustavo Carneiro; Tan
Название: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
ISBN: 3319675575 ISBN-13(EAN): 9783319675572
Издательство: Springer
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Цена: 60550.00 T
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Описание:

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.

The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.


Statistical Learning and Pattern Analysis for Image and Video Processing

Автор: Nanning Zheng; Jianru Xue
Название: Statistical Learning and Pattern Analysis for Image and Video Processing
ISBN: 1447126734 ISBN-13(EAN): 9781447126737
Издательство: Springer
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Цена: 153720.00 T
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Описание: This textbook is an overview of theories, methodologies, and recent developments in the field, covering the theoretical foundation and providing a complete summary of the latest advances. It also presents key issues to be considered in making a real system.

Face Image Analysis by Unsupervised Learning

Автор: Marian Stewart Bartlett
Название: Face Image Analysis by Unsupervised Learning
ISBN: 1461356539 ISBN-13(EAN): 9781461356530
Издательство: Springer
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Цена: 93160.00 T
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Описание: Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis.

Guide to Medical Image Analysis

Автор: Toennies
Название: Guide to Medical Image Analysis
ISBN: 1447160967 ISBN-13(EAN): 9781447160960
Издательство: Springer
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Цена: 65210.00 T
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Описание: Practical in approach, this book describes a range of common imaging techniques, reconstruction techniques and image artifacts, reviews image enhancement methods, discusses image transfer and archiving, and includes exercises and a glossary of abbreviations.

Decision forests for computer vision and medical image analysis

Название: Decision forests for computer vision and medical image analysis
ISBN: 1447149289 ISBN-13(EAN): 9781447149286
Издательство: Springer
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Цена: 149060.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical, easy-to-follow book reviews the theoretical underpinnings of decision forests, organizing the existing literature in a new, general-purpose forest model. Includes exercises and experiments; slides, videos and more reside at a companion website.

Shape Analysis in Medical Image Analysis

Автор: Shuo Li; Jo?o Manuel R. S. Tavares
Название: Shape Analysis in Medical Image Analysis
ISBN: 3319038125 ISBN-13(EAN): 9783319038124
Издательство: Springer
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Цена: 111790.00 T
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Описание: A landmark publication in its scope, this book features contributions by more than a dozen internationally renowned experts, addressing key topics in shape analysis in medical imaging, such as image segmentation, modeling, and classification techniques.

Medical Image Understanding and Analysis

Автор: Mar?a Vald?s Hern?ndez; V?ctor Gonz?lez-Castro
Название: Medical Image Understanding and Analysis
ISBN: 3319609637 ISBN-13(EAN): 9783319609638
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book constitutes the refereed proceedings of the 21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017, held in Edinburgh, UK, in July 2017.
The 82 revised full papers presented were carefully reviewed and selected from 105 submissions. The papers are organized in topical sections on retinal imaging, ultrasound imaging, cardiovascular imaging, oncology imaging, mammography image analysis, image enhancement and alignment, modeling and segmentation of preclinical, body and histological imaging, feature detection and classification.
The chapters 'Model-Based Correction of Segmentation Errors in Digitised Histological Images' and 'Unsupervised Superpixel-Based Segmentation of Histopathological Images with Consensus Clustering' are open access under a CC BY 4.0 license.


Fetal, Infant and Ophthalmic Medical Image Analysis

Автор: M. Jorge Cardoso; Tal Arbel; Andrew Melbourne; Hrv
Название: Fetal, Infant and Ophthalmic Medical Image Analysis
ISBN: 3319675605 ISBN-13(EAN): 9783319675602
Издательство: Springer
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Цена: 51230.00 T
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Описание:

This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.

The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis.


Color Medical Image Analysis

Автор: M. Emre Celebi; Gerald Schaefer
Название: Color Medical Image Analysis
ISBN: 940178129X ISBN-13(EAN): 9789401781299
Издательство: Springer
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Цена: 113180.00 T
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Описание: Recently, medical imaging modalities that use color information have been introduced to the formerly monochrome world of x-ray, CT and ultrasound. This book summarizes the state of the art in the utilization of color information in medical image analysis.

Decision Forests for Computer Vision and Medical Image Analysis

Автор: Antonio Criminisi; J Shotton
Название: Decision Forests for Computer Vision and Medical Image Analysis
ISBN: 144716962X ISBN-13(EAN): 9781447169628
Издательство: Springer
Рейтинг:
Цена: 116450.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical, easy-to-follow book reviews the theoretical underpinnings of decision forests, organizing the existing literature in a new, general-purpose forest model. Includes exercises and experiments; slides, videos and more reside at a companion website.


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