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Inverse Radiosurgery Treatment Planning Through Deconvolution and Constrained Optimization

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Frontiers in Pde-Constrained Optimization

This volume provides a broad and uniform introduction of PDE-constrained optimization as well as to document a number of interesting and;

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Bayesian Deconvolution of Sparse Processes

Bayesian Deconvolution of Sparse Processes: In this work, various Bayesian methods for deconvolution and blind deconvolution of sparse;

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A First Course in Optimization

fundamental problems of constrained and unconstrained optimization as well as linear and convex programming. It also presents basic iterative solution;

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Robotic Radiosurgerytreating Prostate Cancer And Related Gen

The treatment of prostate cancer continues to be problematic owing to serious side-effects, including erectile dysfunction and urinary;

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Evolutionary Constrained Optimization

; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition;

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Approximate Deconvolution Models of Turbulence

This volume presents a mathematical development of a recent approach to the modeling and simulation of turbulent flows based on methods for;

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Bayesian Missing Data Problems

. This book offers a unified treatment of an array of statistical problems that involve missing data and constrained parameters. It shows how;

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Bayesian Missing Data Problems

. This book offers a unified treatment of an array of statistical problems that involve missing data and constrained parameters. It shows how;

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Explanation Constrained Optimization Eco

. Morgan's Explanation of Constrained Optimization for Economists solves this problem by emphasizing explanations, both written and visual, of the;

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Alternating Direction Method of Multipliers for Machine Learning

of optimization problem, and the alternating direction method of multipliers (ADMM) is a commonly used algorithm to solve constrained problems, especially;

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Large-Scale Inverse Problems and Quantification of Uncertainty

-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: * Brings together the perspectives;

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Inverse Problems

. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian;

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Inverse Problems in Vision and 3D Tomography

quantities through the forward problem. This book focuses on imagery and vision problems that can be clearly written in terms of an inverse problem;

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Gamma Knife Radiosurgery

Gamma knife radiosurgery has grown continually in importance in recent years. However, there was a lack of established clinical and;

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Reconstructive Neurosurgery

the role played by imanging for deep brain stimulation targeting in mental illness, using radiosurgery in decompresssion in the treatment;

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Numerical Optimization

, concentrating on methods for both unconstrained and constrained optimization.;

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Numerical Optimization

, concentrating on methods for both unconstrained and constrained optimization.;

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Handbook of Convex Optimization Methods in Imaging Science

This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization;

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Proton Therapy and Radiosurgery

The book is divided into two parts: Part I deals with the relevant physics and planning algorithms of protons (H Breuer) and Part II with;

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Robot Learning by Visual Observation

abstraction * Discusses methods for optimization of task reproduction, such as reformulation of task planning as a constrained optimization problem;

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Shaped Beam Radiosurgery

shaped tumors. This book provides a complete guide to radiosurgery treatments with Novalis. After a thorough discussion of the clinical and;

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Nonlinear Programming: Analysis And Methods

concerns techniques for numerical solutions and unconstrained optimization methods, and it presents commonly used algorithms for constrained;

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Real-Time PDE-Constrained Optimization

-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these;

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Advances in Radiosurgery

about the state-of-the-art of radiosurgical treatment of a multitude of intracranial problems such as arteriovenous malformations, pituitary and;

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Bayesian Approach to Inverse Problems

address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions;

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Strategies for Radiation Therapy Treatment Planning

Strategies for Radiation Therapy Treatment Planning provides radiation oncologists, physicists, and dosimetrists with a step-by-step guide;

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