Decision Forests for Computer Vision and Medical Image Analysis PDF Download
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Author: Antonio Criminisi
Publisher: Springer Science & Business Media
ISBN: 1447149297
Category : Computers
Languages : en
Pages : 367
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Book Description
This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.
Author: Antonio Criminisi
Publisher: Springer Science & Business Media
ISBN: 1447149297
Category : Computers
Languages : en
Pages : 367
Get Book Here
Book Description
This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.
Author: Antonio Criminisi
Publisher: Foundations and Trends(r) in C
ISBN: 9781601985408
Category : Computers
Languages : en
Pages : 162
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Book Description
Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis.
Author: Bjoern Menze
Publisher: Springer
ISBN: 3642184219
Category : Computers
Languages : en
Pages : 235
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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2010, held in Beijing, China, in September 2010 as a satellite event of the 13th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2010. The 10 revised full papers and 11 revised poster papers presented were carefully reviewed and selected from 38 initial submissions. The papers explore the use of modern image recognition technology in tasks such as semantic anatomy parsing, automatic segmentation and quantification, anomaly detection and categorization, data harvesting, semantic navigation and visualization, data organization and clustering, and general-purpose automatic understanding of medical images.
Author: Alejandro Frangi
Publisher: Academic Press
ISBN: 0128136588
Category : Technology & Engineering
Languages : en
Pages : 700
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Book Description
Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing
Author: Bjoern Menze
Publisher: Springer
ISBN: 3319055305
Category : Computers
Languages : en
Pages : 231
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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on Medical Computer Vision, MCV 2013, held in Nagoya, Japan, in September 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013. The 7 revised full papers and 12 poster papers presented were selected from 25 submissions. They have been organized in topical sections on registration and visualization, segmentation, detection and localization, and features and retrieval. In addition, the volume contains two invited papers describing segmentation task and data set of the VISCERAL benchmark challenge.
Author:
Publisher: BoD – Books on Demand
ISBN: 1789233305
Category : Medical
Languages : en
Pages : 136
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Book Description
This book deals with medical image analysis methods. In particular, it contains two significant chapters on image segmentation as well as some selected examples of the application of image analysis and processing methods. Despite the significant development of information technology methods used in modern image analysis and processing algorithms, the segmentation process remains open. This is mainly due to intra-patient variability and/or scene diversity. Segmentation is equally difficult in the case of ultrasound imaging and depends on the location of the probe or the contact force. Regardless of the imaging method, segmentation must be tailored for a specific application in almost every case. These types of application areas for various imaging methods are included in this book.
Author: S. Kevin Zhou
Publisher: Academic Press
ISBN: 0128026766
Category : Computers
Languages : en
Pages : 548
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Book Description
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
Author: Kensaku Mori
Publisher: Springer
ISBN: 3642407609
Category : Computers
Languages : en
Pages : 708
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Book Description
The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 81 papers included in the third volume have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing; imaging, reconstruction, and enhancement; segmentation; physiological modeling, simulation, and planning; intraoperative guidance and robotics; microscope, optical imaging, and histology; diffusion MRI; brain segmentation and atlases; and functional MRI and neuroscience applications.
Author: Polina Golland
Publisher: Springer
ISBN: 3319104705
Category : Computers
Languages : en
Pages : 854
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Book Description
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.
Author: Henning Müller
Publisher: Springer
ISBN: 3319611887
Category : Computers
Languages : en
Pages : 227
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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016. The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions. The goal of the MCV workshop is to explore the use of "big data” algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images. The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.
