Deformable Models for Volume Feature Tracking
Author | : Gregory James Klein |
Publisher | : |
Total Pages | : 240 |
Release | : 1999 |
Genre | : |
ISBN | : |
Download Deformable Models for Volume Feature Tracking Book in PDF, ePub and Kindle
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Deformable Models For Volume Feature Tracking PDF full book. Access full book title Deformable Models For Volume Feature Tracking.
Author | : Gregory James Klein |
Publisher | : |
Total Pages | : 240 |
Release | : 1999 |
Genre | : |
ISBN | : |
Author | : Aly Farag |
Publisher | : Springer |
Total Pages | : 556 |
Release | : 2007-08-02 |
Genre | : Medical |
ISBN | : 9780387312019 |
This book covers the complete spectrum of deformable models, its evolution as an imagery field and its use in many biomedical engineering and clinical application disciplines. It includes level sets, PDEs, curve and surface evolution and their applications in biomedical fields covering both static and motion imagery.
Author | : Aly Farag |
Publisher | : Springer Science & Business Media |
Total Pages | : 563 |
Release | : 2007-08-21 |
Genre | : Medical |
ISBN | : 0387684131 |
This book covers the complete spectrum of deformable models, its evolution as an imagery field and its use in many biomedical engineering and clinical application disciplines. It includes level sets, PDEs, curve and surface evolution and their applications in biomedical fields covering both static and motion imagery.
Author | : Manuel González Hidalgo |
Publisher | : Springer Science & Business Media |
Total Pages | : 301 |
Release | : 2012-10-29 |
Genre | : Computers |
ISBN | : 9400754469 |
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.
Author | : Xiao Yu Chen |
Publisher | : |
Total Pages | : 260 |
Release | : 2008 |
Genre | : Deformations (Mechanics) |
ISBN | : |
Author | : Jianping Cai |
Publisher | : Springer |
Total Pages | : 107 |
Release | : 2018-07-07 |
Genre | : Computers |
ISBN | : 9783319845494 |
This book covers dynamic simulation of deformable objects, which is one of the most challenging tasks in computer graphics and visualization. It focuses on the simulation of deformable models with anisotropic materials, one of the less common approaches in the existing research. Both physically-based and geometrically-based approaches are examined. The authors start with transversely isotropic materials for the simulation of deformable objects with fibrous structures. Next, they introduce a fiber-field incorporated corotational finite element model (CLFEM) that works directly with a constitutive model of transversely isotropic material. A smooth fiber-field is used to establish the local frames for each element. To introduce deformation simulation for orthotropic materials, an orthotropic deformation controlling frame-field is conceptualized and a frame construction tool is developed for users to define the desired material properties. The orthotropic frame-field is coupled with the CLFEM model to complete an orthotropic deformable model. Finally, the authors present an integrated real-time system for animation of skeletal characters with anisotropic tissues. To solve the problems of volume distortion and high computational costs, a strain-based PBD framework for skeletal animation is explained; natural secondary motion of soft tissues is another benefit. The book is written for those researchers who would like to develop their own algorithms. The key mathematical and computational concepts are presented together with illustrations and working examples. It can also be used as a reference book for graduate students and senior undergraduates in the areas of computer graphics, computer animation, and virtual reality. Academics, researchers, and professionals will find this to be an exceptional resource.
Author | : Anthony James Heap |
Publisher | : |
Total Pages | : |
Release | : 1997 |
Genre | : |
ISBN | : |
The use of computer vision to locate or track objects in images has applications in a diversity of domains. It is generally recognised that the analysis of objects of interest is eased significantly by making use of models of objects. In many cases, the strongest visual feature of an object is its shape. Also, many objects of interest are non-rigid, or have a non-rigid appearance with respect to a particular viewpoint. For these reasons, there is much interest in the construction of, and tracking with, deformable shape models. A common approach to building such a model is to apply statistics to a set of real-life training examples of an object in order to learn shape and deformation characteristics. Such methods have proved successful in many specific applications; however, they can experience inadequacies in the general case. For example, objects which exhibit non-linear deformations give rise to models which are not compact and not specific: in the process of capturing the range of valid shapes, invalid shapes also become incorporated into the model. This effect is particularly pronounced when building models from automatically-gathered training data. Also, in tracking, smooth movement and deformation is generally assumed, but is not always the case: the apparent shape of an object can change discontinuously over time due to, for example, rotations in 3D. The work in this thesis addresses the above problems. Two extensions to current statistical methods are described. The first makes use of polar coordinates to improve the modelling of objects which bend or pivot. The second uses a hierarchical approach to model more general complex deformations; non-linearities are broken down into smaller linear pieces in order to improve model specificity. In particular, this greatly improves the modelling of objects from automatically-gathered training data. A new approach to tracking which complements the latter of these models is also described. Learned object shape dynamics are combined with stochastic tracking to produce a system which can track from automatically-generated models, as well as being able to handle discontinuous shape changes. Examples are given of the use of these techniques, predominantly in the domain of hand tracking. In particular, it is shown how it is possible to track 3D objects purely from 2D models of their silhouettes.
Author | : Douglas DeCarlo |
Publisher | : |
Total Pages | : |
Release | : 1997 |
Genre | : |
ISBN | : |
Author | : Aly Farag |
Publisher | : Springer |
Total Pages | : 1142 |
Release | : 2007-08-02 |
Genre | : Technology & Engineering |
ISBN | : 9780387721491 |
This two-volume set on Deformable Models: Biomedical and Clinical Applications & Theory and Biomaterial Applications provides a wide cross-section of the methods and algorithms of variational and PDE methods in biomedical image analysis. The chapters are written by well-known researchers in this field, and the presentation style goes beyond an intricate abstraction of the theory into real application of the methods and description of the algorithms that were implemented. As such these chapters will serve the main goal of the editors of these two volumes in bringing down to earth the latest in variational and PDE methods in modeling of soft tissues. Overall, the thirty-one chapters in the two volumes provide an elegant crosssection of the theory and application of variational and PDE approaches in medical image analysis. Graduate students and researchers at various levels of familiarity with these techniques will find the two volumes very useful for understanding the theory and algorithmic implementations. In addition, the various case studies provided demonstrate the power of these techniques in clinical applications. Researchers at various levels will find these chapters useful to understand the theory, algorithms, and implementation of many of these approaches.
Author | : David Wilson |
Publisher | : Springer Science & Business Media |
Total Pages | : 661 |
Release | : 2006-10-28 |
Genre | : Medical |
ISBN | : 0306485516 |
Handbook of Biomedical Image Analysis: Segmentation Models (Volume I) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry . Key Features: - Principles of intra-vascular ultrasound (IVUS) - Principles of positron emission tomography (PET) - Physical principles of magnetic resonance angiography (MRA). - Basic and advanced level set methods - Shape for shading method for medical image analysis - Wavelet transforms and other multi-scale analysis functions - Three dimensional deformable surfaces - Level Set application for CT lungs, brain MRI and MRA volume segmentation - Segmentation of incomplete tomographic medical data sets - Subjective level sets for missing boundaries for segmentation