Biomedical Visualisation
Biomedical Visualisation

Author: Paul M. Rea

Publisher: Springer Nature

Published: 2022-02-11

Total Pages: 351

ISBN-13: 3030877795

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This edited book explores the use of technology to enable us to visualise the life sciences in a more meaningful and engaging way. It will enable those interested in visualisation techniques to gain a better understanding of the applications that can be used in visualisation, imaging and analysis, education, engagement and training. The reader will also be able to learn about the use of visualisation techniques and technologies for the historical and forensic settings. The chapters presented in this volume cover such a diverse range of topics, with something for everyone. We present here chapters on 3D visualising novel stent grafts to aid treatment of aortic aneuryms; confocal microscopy constructed vascular models in patient education; 3D patient specific virtual reconstructions in surgery; virtual reality in upper limb rehabilitation in patients with multiple sclerosis and virtual clinical wards. In addition, we present chapters in artificial intelligence in ultrasound guided regional anaesthesia; carpal tunnel release visualisation techniques; visualising for embryology education and artificial intelligence data on bone mechanics. Finally we conclude with chapters on visualising patient communication in a general practice setting; digital facial depictions of people from the past; instructor made cadaveric videos, novel cadaveric techniques for enhancing visualisation of the human body and finally interactive educational videos and screencasts. This book explores the use of technologies from a range of fields to provide engaging and meaningful visual representations of the biomedical sciences. It is therefore an interesting read for researchers, developers and educators who want to learn how visualisation techniques can be used successfully for a variety of purposes, such as educating students or training staff, interacting with patients and biomedical procedures in general.

Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems
Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems

Author: Yinpeng Wang

Publisher: CRC Press

Published: 2023-07-06

Total Pages: 200

ISBN-13: 100089665X

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This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems. Pursuing a holistic perspective, the book includes the following areas. The first chapter discusses the basic DL frameworks. Then, the steady heat conduction problem is solved by the classical U-net in Chapter 2, involving both the passive and active cases. Afterwards, the sophisticated heat flux on a curved surface is reconstructed by the presented Conv-LSTM, exhibiting high accuracy and efficiency. Additionally, a physics-informed DL structure along with a nonlinear mapping module are employed to obtain the space/temperature/time-related thermal conductivity via the transient temperature in Chapter 4. Finally, in Chapter 5, a series of the latest advanced frameworks and the corresponding physics applications are introduced. As deep learning techniques are experiencing vigorous development in computational physics, more people desire related reading materials. This book is intended for graduate students, professional practitioners, and researchers who are interested in DL for computational physics.

Model Reduction and Approximation
Model Reduction and Approximation

Author: Peter Benner

Publisher: SIAM

Published: 2017-07-06

Total Pages: 421

ISBN-13: 161197481X

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Many physical, chemical, biomedical, and technical processes can be described by partial differential equations or dynamical systems. In spite of increasing computational capacities, many problems are of such high complexity that they are solvable only with severe simplifications, and the design of efficient numerical schemes remains a central research challenge. This book presents a tutorial introduction to recent developments in mathematical methods for model reduction and approximation of complex systems. Model Reduction and Approximation: Theory and Algorithms contains three parts that cover (I) sampling-based methods, such as the reduced basis method and proper orthogonal decomposition, (II) approximation of high-dimensional problems by low-rank tensor techniques, and (III) system-theoretic methods, such as balanced truncation, interpolatory methods, and the Loewner framework. It is tutorial in nature, giving an accessible introduction to state-of-the-art model reduction and approximation methods. It also covers a wide range of methods drawn from typically distinct communities (sampling based, tensor based, system-theoretic).?? This book is intended for researchers interested in model reduction and approximation, particularly graduate students and young researchers.

Numerical Algorithms
Numerical Algorithms

Author: Justin Solomon

Publisher: CRC Press

Published: 2015-06-24

Total Pages: 400

ISBN-13: 1482251892

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Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig

Genetic Programming
Genetic Programming

Author: John R. Koza

Publisher: MIT Press

Published: 1992

Total Pages: 856

ISBN-13: 9780262111706

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In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.

Advances in Theory and Practice of Computational Mechanics
Advances in Theory and Practice of Computational Mechanics

Author: Lakhmi C. Jain

Publisher: Springer Nature

Published: 2020-03-31

Total Pages: 386

ISBN-13: 9811526001

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This book discusses physical and mathematical models, numerical methods, computational algorithms and software complexes, which allow high-precision mathematical modeling in fluid, gas, and plasma mechanics; general mechanics; deformable solid mechanics; and strength, destruction and safety of structures. These proceedings focus on smart technologies and software systems that provide effective solutions to real-world problems in applied mechanics at various multi-scale levels. Highlighting the training of specialists for the aviation and space industry, it is a valuable resource for experts in the field of applied mathematics and mechanics, mathematical modeling and information technologies, as well as developers of smart applied software systems.

Advances in Intelligent Data Analysis
Advances in Intelligent Data Analysis

Author: Frank Hoffmann

Publisher: Springer

Published: 2003-06-30

Total Pages: 395

ISBN-13: 3540448160

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This book constitutes the refereed proceedings of the 4th International Conference on Intelligent Data Analysis, IDA 2001, held in Cascais, Portugal, in September 2001.The 37 revised full papers presented were carefully reviewed and selected from a total of almost 150 submissions. All current aspects of this interdisciplinary field are addressed; the areas covered include statistics, artificial intelligence, neural networks, machine learning, data mining, and interactive dynamic data visualization.

Computational Geometry
Computational Geometry

Author: Mark de Berg

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 370

ISBN-13: 3662042452

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This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.