Natural User Interfaces in Medical Image Analysis, Marek R. Ogiela; Tomasz Hachaj
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: 17468.00 р. 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.
Автор: Shuo Li; Jo?o Manuel R. S. Tavares Название: Shape Analysis in Medical Image Analysis ISBN: 3319375210 ISBN-13(EAN): 9783319375212 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
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 Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: David Zhang; Dongmin Guo; Ke Yan Название: Breath Analysis for Medical Applications ISBN: 9811043213 ISBN-13(EAN): 9789811043215 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes breath signal processing technologies and their applications in medical sample classification and diagnosis.
Автор: M. Emre Celebi; Gerald Schaefer Название: Color Medical Image Analysis ISBN: 940178129X ISBN-13(EAN): 9789401781299 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Yefeng Zheng; Dorin Comaniciu Название: Marginal Space Learning for Medical Image Analysis ISBN: 1493955756 ISBN-13(EAN): 9781493955756 Издательство: Springer Рейтинг: Цена: 11179.00 р. 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.
Автор: Toennies Название: Guide to Medical Image Analysis ISBN: 1447160967 ISBN-13(EAN): 9781447160960 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
Автор: Shuo Li; Jo?o Manuel R. S. Tavares Название: Shape Analysis in Medical Image Analysis ISBN: 3319038125 ISBN-13(EAN): 9783319038124 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Allan Hanbury; Henning M?ller; Georg Langs Название: Cloud-Based Benchmarking of Medical Image Analysis ISBN: 3319496425 ISBN-13(EAN): 9783319496429 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: VISCERAL: Evaluation-as-a-Service for Medical Imaging.- Using the Cloud as a Platform for Evaluation and Data Preparation.- Ethical and Privacy Aspects of Using Medical Image Data.- Annotating Medical Image Data.- Datasets created in VISCERAL.- Evaluation Metrics for Medical Organ Segmentation and Lesion Detection.- VISCERAL Anatomy Benchmarks for Organ Segmentation and Landmark Localisation: Tasks and Results.- Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark.- Automatic Atlas-Free Multi-Organ Segmentation of Contrast-Enhanced CT Scans.- Multi-organ Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information.- Automatic Multi-organ Segmentation using Hierarchically-Registered Probabilistic Atlases.- Multi-Atlas Segmentation Using Robust Feature-Based Registration.- Combining Radiology Images and Clinical Meta-data for Multimodal Medical Case-based Retrieval.- Text and Content-based Medical Image Retrieval in the VISCERAL Retrieval Benchmark.
Автор: Chan, Tony F. Jianhong, Shen Название: Image processing and analysis ISBN: 089871589X ISBN-13(EAN): 9780898715897 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 12540.00 р. Наличие на складе: Нет в наличии.
Описание: This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.
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