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Deformation Models
The computational modelling of deformations has been actively studied for the last thirty years. This is mainly due to its large range of applications that include computer animation, medical imaging, shape estimation, face deformation as well as other parts of the human body, and object tracking. In addition, these advances have been supported by the evolution of computer processing capabilities, enabling realism in a more sophisticated way. This book encompasses relevant works of expert researchers in the field of deformation models and their applications. The book is divided into two main parts. The first part presents recent object deformation techniques from the point of view of computer graphics and computer animation. The second part of this book presents six works that study deformations from a computer vision point of view with a common characteristic: deformations are applied in real world applications. The primary audience for this work are researchers from different multidisciplinary fields, such as those related with Computer Graphics, Computer Vision, Computer Imaging, Biomedicine, Bioengineering, Mathematics, Physics, Medical Imaging and Medicine.
Geometric Modeling for Scientific Visualization
Geometric Modeling and Scientific Visualization are both established disciplines, each with their own series of workshops, conferences and journals. But clearly both disciplines overlap; this observation led to the idea of composing a book on Geometric Modeling for Scientific Visualization.
Mobile Sensing in Psychology
How can large-scale, real-time, and real-world data on people’s behaviors, interactions, and environments improve psychological measurement, or lead to customized psychological interventions? Written expressly for social and behavioral scientists, this cutting-edge handbook describes the key concepts and tools of mobile sensing and explains how to plan and conduct a mobile sensing study. Renowned experts address the whats, whys, and how-tos of collecting "big data" using smartphones and other wearables, and explore which research questions can best be addressed with these tools. Modern statistical methods for analyzing mobile sensing data are described--for example, dynamic structural equation modeling, network modeling, and machine learning, including deep neural networks. The book includes best-practice research examples of applications in clinical psychology, aging, neuroscience, health, emotions, relationships, personality, the workplace, and other areas. Key methodological challenges and ethical/privacy issues are highlighted throughout.
Artificial Intelligence Research and Development
The field covered by Artificial Intelligence (AI) is multiform and gathers subjects as various as the engineering of knowledge, the automatic treatment of the language, the training and the systems multiagents, and more. This book focuses on subjects including Machine Learning, Reasoning, Neural Networks, Computer Vision, and Multiagent Systems.
Functional Imaging and Modeling of the Heart
The refereed proceedings of the Second International Workshop on Functional Imaging and Modeling of the Heart, FIMH 2003, held in Lyon, France in June 2003. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected for presentation. The papers are organized in topical sections on anatomy extraction and description, modeling of the cardiac mechanics and functions, electro-physiology and electro- and magnetography, motion estimation, image registration and image analysis, and data acquisition and experimental and modeling issues.
Signal Processing and Machine Learning for Biomedical Big Data
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzin...
Frontiers Of Medical Imaging
There has been great progress and increase in demand for medical imaging. The aim of this book is to capture all major developments in all aspects of medical imaging. As such, this book consists of three major parts: medical physics which includes 3D reconstructions, image processing and segmentation in medical imaging, and medical imaging instruments and systems. As the field is very broad and growing exponentially, this book will cover major activities with chapters prepared by leaders in the field.This book takes a balanced approach in providing coverage of all major work done in the field, and thus provides readers a clear view of the frontier activities in the field. Other books may only focus on instrumentation, physics or computer algorithms. In contrast, this book contains all components so that the readers will obtain a full picture of the field. At the same time, readers can gain some deep insights into certain special topics such as 3D reconstruction and image enhancement software systems involving MRI, ultrasound, X-ray and other medical imaging modalities.
Pattern Recognition and Image Analysis
This volume constitutes the refereed proceedings of the 5th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2011, held in Las Palmas de Gran Canaria, Spain, in June 2011. The 34 revised full papers and 58 revised poster papers presented were carefully reviewed and selected from 158 submissions. The papers are organized in topical sections on computer vision; image processing and analysis; medical applications; and pattern recognition.
Topics in Artificial Intelligence
This book constitutes the refereed proceedings of the 5th Catalonian Conference on Artificial Intelligence, CCIA 2002, held in Castellón, Spain in October 2002. The 37 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers are organized in topical sections on reasoning models, constraint satisfation, machine learning and classification, multi-agent systems, and computer vision and robotics.
Plaque Imaging
This publication starts of with a review of plaque imaging techniques, with an introduction of the segmentation techniques for plaque classification and quantification. Many aspects of plaque imaging techniques are presented in this publication, such as; medical image retrieval and database management, MRI techniques to differentiate stable versus high risk atherosclerosis, composition and morphology of atherosclerotic plaque, analysis of the soft tissue based on computer vision techniques, modelling of coronary artery biomechanics, Cardiac CT for the assessment of cardiovascular pathology with an emphasis on the detection of coronary atherosclerosis, technical and practical issues regarding coronary atherosclerotic plaque imaging by CT (focussing on coronary calcium imaging), feasibility of a non-invasive, in vivo determination of the IBS of arterial wall tissue, high resolution ultrasound images of carotid plaques, the problem of reliable features extraction and classification process and a discussion on advanced mathematical techniques to extract spectral information from the RF data to determine the plaque composition.
