Description

Book Synopsis

CI Techniques & Algorithms for a Variety of Medical Imaging Situations
Documents recent advances and stimulates further research

A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches.

The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary optimization techniques, rough sets, support vector machines, tabu search, fuzzy logic, a Bayesian probabilistic framework, a statistical parts-based appearance model, a reinforcement learning-based multistage image segmentation algorithm, a machine learn

Trade Review

In choosing this book the reader will be exposed to the range of exciting research that is being conducted in the context of medical imaging. … I am sure that this collection of the latest trends and developments will further stimulate discussion and development of new solutions. The book will be of interest and relevance to anyone involved in the computational analysis and interpretation of images—whether medical or not.
International Statistical Review, 2009



Table of Contents

Preface. Computational Intelligence on Medical Imaging with Artificial Neural Networks. Evolutionary Computing and Its Use in Medical Imaging. Rough Sets in Medical Imaging: Foundations and Trends. Early Detection of Wound Inflammation by Color Analysis. Analysis and Applications of Neural Networks for Skin Lesion Border Detection. Prostate Cancer Classification Using Multispectral Imagery and Metaheuristics. Intuitionistic Fuzzy Processing of Mammographic Images. Fuzzy C-Means and Its Applications in Medical Imaging. Image Informatics for Clinical and Preclinical Biomedical Analysis. Parts-Based Appearance Modeling of Medical Imagery. Reinforced Medical Image Segmentation. Image Segmentation and Parameterization for Automatic Diagnostics of Whole-Body Scintigrams: Basic Concepts. Distributed 3-D Medical Image Registration Using Intelligent Agents. Monte Carlo-Based Image Reconstruction in Emission Tomography. Deformable Organisms: An Artificial Life Framework for Automated Medical Image Analysis. Index.

Computational Intelligence in Medical Imaging

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    £180.50

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    RRP £190.00 – you save £9.50 (5%)

    Order before 4pm today for delivery by Thu 30 Jul 2026.

    A Hardback by G. Schaefer, A. Hassanien, J. Jiang

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      Publisher: Taylor & Francis Ltd
      Publication Date: Publication Date: 24/03/2009
      ISBN13: 9781420060591, 978-1420060591
      ISBN10: 1420060597

      Description

      Book Synopsis

      CI Techniques & Algorithms for a Variety of Medical Imaging Situations
      Documents recent advances and stimulates further research

      A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches.

      The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary optimization techniques, rough sets, support vector machines, tabu search, fuzzy logic, a Bayesian probabilistic framework, a statistical parts-based appearance model, a reinforcement learning-based multistage image segmentation algorithm, a machine learn

      Trade Review

      In choosing this book the reader will be exposed to the range of exciting research that is being conducted in the context of medical imaging. … I am sure that this collection of the latest trends and developments will further stimulate discussion and development of new solutions. The book will be of interest and relevance to anyone involved in the computational analysis and interpretation of images—whether medical or not.
      International Statistical Review, 2009



      Table of Contents

      Preface. Computational Intelligence on Medical Imaging with Artificial Neural Networks. Evolutionary Computing and Its Use in Medical Imaging. Rough Sets in Medical Imaging: Foundations and Trends. Early Detection of Wound Inflammation by Color Analysis. Analysis and Applications of Neural Networks for Skin Lesion Border Detection. Prostate Cancer Classification Using Multispectral Imagery and Metaheuristics. Intuitionistic Fuzzy Processing of Mammographic Images. Fuzzy C-Means and Its Applications in Medical Imaging. Image Informatics for Clinical and Preclinical Biomedical Analysis. Parts-Based Appearance Modeling of Medical Imagery. Reinforced Medical Image Segmentation. Image Segmentation and Parameterization for Automatic Diagnostics of Whole-Body Scintigrams: Basic Concepts. Distributed 3-D Medical Image Registration Using Intelligent Agents. Monte Carlo-Based Image Reconstruction in Emission Tomography. Deformable Organisms: An Artificial Life Framework for Automated Medical Image Analysis. Index.

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