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Stochastic Modeling for Medical Image Analysis

Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided;

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Stochastic Geometry for Image Analysis

This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process;

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Computational Vision and Medical Image Processing IV

, modal analyses, stochastic methods, principal and independent components analysis and distribution models. Computational Vision and Medical;

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Bayesian and grAphical Models for Biomedical Imaging

or for the advancement of modeling and analysis of medical imaging data.;

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Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications

talks were carefully reviewed and selected from 54 submissions. The papers cover the following topics: medical treatment, imaging and analysis;

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Image-Based Geometric Modeling and Mesh Generation

. It is well known that FEM is currently well-developed and efficient, but mesh generation for complex geometries (e.g., the human body) still;

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Circuits, Signals, and Systems for Bioengineers

chapters have been added on image analysis, noise, stochastic processes and ergodicity, and new medical examples and applications are included;

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Medical Image Analysis and Informatics

With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image;

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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 Part I

feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration;

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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 7-21, 2016, Proceedings, Part II

feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration;

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Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2016 Part III

feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration;

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Computational Vision and Medical Image Processing

Imaging; Virtual Reality; Software Development for Image Processing and Analysis; Computer Aided Diagnosis, Surgery, Therapy and Treatment;

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Stochastic Partial Differential Equations for Computer Vision with Uncertain Data

computer vision with stochastic images (Chapter 6), and demonstrate the use of these principles for accomplishing sensitivity analysis (Chapter 7;

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Computational Vision and Medical Image Processing

Compression; - Image Processing and Analysis; - Image Segmentation; - Medical Imaging; - Motion and Deformation Analysis; - Objects Simulation;

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Computational Vision and Medical Image Processing

, Acquisition and Compression; Objects Simulation; Virtual Reality; Software Development for Image Processing and Analysis; Computer Aided Diagnosis;

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Handbook of Medical Image Processing and Analysis

The Handbook of Medical Image Processing and Analysis is a comprehensive compilation of concepts and techniques used for processing and;

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Computational Vision and Medical Image Processing

Imaging; Virtual Reality; Software Development for Image Processing and Analysis; Computer Aided Diagnosis, Surgery, Therapy and Treatment;

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Computational Modelling of Objects Represented in Images III

, Registration and Compression; - Image Enhancement and Restoring; - Image Processing and Analysis; - Image Segmentation; - Medical Imaging;

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Modeling and Management of Stochastic Systems

of exceptional investigations in different aspects of stochastic systems and their behavior. It presents a distinct analysis on practical aspects;

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Computational Bioengineering and Bioinformatics

prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for;

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Computational Bioengineering and Bioinformatics

prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for;

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Recent Advances In Stochastic Modeling And Data Analysis

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover;

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Stochastic Optimization

Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic;

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Deep Learning for Medical Image Analysis

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This;

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Computer Analysis of Images and Patterns

multimedia, model-based vision approaches, motion analysis, natural computation for digital imagery, segmentation and grouping, and shape;

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Computer Analysis of Images and Patterns

multimedia, model-based vision approaches, motion analysis, natural computation for digital imagery, segmentation and grouping, and shape;

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Technologies for Medical Sciences

important technologies for medical sciences, including: computational modeling and simulation, image processing and analysis, medical imaging, human;

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