biomedical image analysis machine (29 Ergebnisse)

Zustand: New.

Zustand: New. SUPER FAST SHIPPING.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Zustand: New. In.

PF. Zustand: New.

Zustand: New.

Zustand: New. pp. XVII, 222 104 illus., 75 illus. in color. 1 Edition NO-PA16APR2015-KAP.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: Brand New. 222 pages. 9.25x6.10x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic.For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic.For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

Paperback. Zustand: New. New. book.

Paperback. Zustand: Brand New. 148 pages. 8.66x5.91x0.34 inches. In Stock.

Zustand: New. In.

Zustand: New.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Machine Learning for Biomedical Image Quality Analysis presents a cutting-edge exploration of the applications of machine learning in biomedical image quality analysis. By leveraging the power of machine learning and data analytics, this book examines the potential for machine learning to improve the accuracy and efficiency of biomedical image quality analysis. From image analysis to diagnosis, Machine Learning for Biomedical Image Quality Analysis provides a detailed examination of the current state-of-the-art and the future directions of machine learning in biomedical image quality analysis. By exploring the complex relationships between machine learning, biomedical image quality analysis, and medicine, this book offers a fresh perspective on the possibilities of machine learning in biomedical research and practice. As the field continues to evolve, Machine Learning for Biomedical Image Quality Analysis serves as a crucial resource for researchers, clinicians, and students seeking to understand the latest advancements in machine learning-assisted biomedical image quality analysis. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Machine Learning for Biomedical Image Analysis is a groundbreaking work that harnesses the power of machine learning to revolutionize biomedical image analysis. The book presents a comprehensive overview of machine learning techniques and their applications in the biomedical domain, including image classification, segmentation, and feature extraction. By leveraging machine learning, biomedical image analysis can be transformed into a more accurate, efficient, and effective process. This thought-provoking work challenges readers to rethink the boundaries between machine learning and biomedical image analysis, and to explore the vast potential of machine learning in the biomedical field. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Biomedical image analysis and machine learning techniques are critical components of modern biomedical research, but their development and implementation require sophisticated techniques and tools. Biomedical Image Analysis and Machine Learning Techniques for Biomedical Research provides a comprehensive and authoritative overview of the latest biomedical image analysis and machine learning methods for biomedical research. This book explores the role of biomedical image analysis in disease diagnosis and treatment, as well as its potential for developing novel therapeutic strategies. By providing a detailed and thorough analysis of the latest biomedical image analysis and machine learning techniques, this book equips researchers and clinicians with the knowledge and tools necessary to tackle the challenges of biomedical research. With its cutting-edge research and practical applications, Biomedical Image Analysis and Machine Learning Techniques for Biomedical Research is an essential resource for anyone working in the field of biomedical research. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic.For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts. 244 pp. Englisch.

Zustand: New. Print on Demand pp. XVII, 222 104 illus., 75 illus. in color.

Zustand: New. PRINT ON DEMAND pp. XVII, 222 104 illus., 75 illus. in color.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the medical field, data is increasingly growing and traditional methods cannot manage them efficiently. In the computational biomedical, the continuous challenges are management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of the data using machine learning and artificial intelligence techniques. It becomes very important to develop methods and/or architectures based on big data technologies for complete processing of biomedical images data. In this thesis, we propose a complete and optimal workflow based on big data technology and optimal algorithms drawn from literature to manage biomedical images. Compression step within the proposed optimal workflow will be considered as a study case implementing big data analysis technology. The proposed workflow implements an image compression algorithm for biomedical images, which is based on three main steps, orthogonal transform, vector quantization using machine learning and entropy encoding. The proposed algorithm allows us to develop appropriate and efficient methods to leverage a large number of images into the proposed workflow.

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. It will serve as a leading industry reference.Inhalt.

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues.