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The Resource Soft computing based medical image analysis, Nilanjan Dey, Amira S. Ashour, Fuquian Shi, Valentina E. Balas

Soft computing based medical image analysis, Nilanjan Dey, Amira S. Ashour, Fuquian Shi, Valentina E. Balas

Label
Soft computing based medical image analysis
Title
Soft computing based medical image analysis
Statement of responsibility
Nilanjan Dey, Amira S. Ashour, Fuquian Shi, Valentina E. Balas
Creator
Contributor
Author
Subject
Language
eng
Summary
Soft Computing Based Medical Image Analysis presents the foremost techniques of soft computing in medical image analysis and processing. It includes image enhancement, segmentation, classification-based soft computing, and their application in diagnostic imaging, as well as an extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book introduces the theory and concepts of digital image analysis and processing based on soft computing with real-world medical imaging applications. Comparative studies for soft computing based medical imaging techniques and traditional approaches in medicine are addressed, providing flexible and sophisticated application-oriented solutions
Cataloging source
N$T
http://library.link/vocab/creatorDate
1984-
http://library.link/vocab/creatorName
Dey, Nilanjan
Dewey number
616.07/54
Index
index present
LC call number
RC78.7.D53
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1975-
http://library.link/vocab/relatedWorkOrContributorName
  • Ashour, Amira
  • Shi, Fuquian
  • Balas, Valentina Emilia
http://library.link/vocab/subjectName
  • Diagnostic imaging
  • Diagnostic imaging
Label
Soft computing based medical image analysis, Nilanjan Dey, Amira S. Ashour, Fuquian Shi, Valentina E. Balas
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Front Cover; Soft Computing Based Medical Image Analysis; Copyright; Contents; Contributors; Preface; Acknowledgments; Section A: Medical Image Analysis and Processing; Chapter 1: Computing in Medical Image Analysis; 1. Introduction; 2. Medical Image Segmentation Techniques; 2.1. Histogram-Based Segmentation; 2.2. Region-Based Segmentation; 2.3. Split-and-Merge Segmentation; 2.4. Edge-Based Segmentation; 3. Metaheuristics; 3.1. Genetic Algorithm; 3.2. Particle Swarm Optimization; 3.3. Ant Colony Optimization; 3.4. Bat Optimization Algorithm; 4. Segmentation Algorithms for Medical Images
  • 4.1. Metaheuristics-Based Segmentation of Magnetic Resonance Images4.2. Metaheuristics Based Segmentation of Computed Tomography Images; 5. Conclusion; References; Chapter 2: Automated Pathology Image Analysis; 1. Introduction; 2. Need for Quantitative Image Analysis in Pathology; 2.1. Differences in Radiology and Histopathology Automated Techniques; 2.2. Anomalies in Microscopic Images; 3. Histology-Imaging Technologies; 3.1. Light Microscopy; 3.2. Fluorescence Microscopy; 3.3. Confocal Microscopy; 3.4. Hyperspectral and Multispectral Microscopy; 3.5. Electron Microscopy
  • 3.6. Transmission Electron Microscopes3.7. Scanning Electron Microscopes; 4. Automated Pathology Image Analysis; 4.1. Image Preprocessing; 4.1.1. Color Illumination and Normalization; 4.1.2. Image Enhancement; 4.2. Image Segmentation; 4.2.1. Pathology Image Segmentation; 4.3. Feature Extraction; 4.3.1. Pixel-Level Features; 4.3.2. Object-Level Features; 4.3.3. Semantic-Level Features; 4.4. Feature Selection; 4.4.1. Dimensionality Reduction; 4.5. Image Classification; 5. Pathology Image Data Sources; 5.1. The Cancer Genome Atlas; 5.2. Lung Image Database Consortium
  • 5.3. National Biomedical Imaging Archive (NBIA)5.4. Microscopic Blood Cell Image Dataset (ALL-IDB1, ALL-IDB2); 5.5. DTI Database; 6. Discussion; 7. Future Trends and Open Issues; References; Chapter 3: Multiple Kernel-Learning Approach for Medical Image Analysis; 1. Introduction; 2. Related Literature; 3. Nature and Characteristics of Biomedical Images; 3.1. Image Characteristics; 3.2. Medical Imaging Modalities; 3.3. Image Noise; 4. Feature Extraction and Image Descriptors; 4.1. Image Descriptors; 5. Computer-Aided Diagnosis; 6. Kernel-Based Machine Learning; 6.1. Basics in Machine Learning
  • 6.1.1. Classification and Regression6.1.2. Cost Function; 6.2. Similarity Measures and Features; 6.3. Kernels; 6.4. Kernel Trick; 6.5. Kernel Matrix; 7. Multiple Kernel-Learning Model; 7.1. 1-Norm Soft-Margin SVM; 7.2. MKL Optimization Using SDP; 8. Multiple Kernel Learning for Biomedical Image Analysis; 8.1. Open-Source Computer Vision; 8.2. Shogun Machine-Learning Toolbox; 8.3. Case Study; 8.3.1. Dataset; 8.3.2. Experiment; 9. Discussion; 9.1. Limitations; 9.2. Future Challenges; 10. Conclusion; Acknowledgments; References; Further Reading; Section B: Medical Image Enhancement
Control code
SCIDI1020172347
Dimensions
unknown
Edition
First edition.
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9780128131749
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
Online access with subscription: Elsevier (Sciencedirect Freedom Collection)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1020172347
  • (OCoLC)1020172347
Label
Soft computing based medical image analysis, Nilanjan Dey, Amira S. Ashour, Fuquian Shi, Valentina E. Balas
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Front Cover; Soft Computing Based Medical Image Analysis; Copyright; Contents; Contributors; Preface; Acknowledgments; Section A: Medical Image Analysis and Processing; Chapter 1: Computing in Medical Image Analysis; 1. Introduction; 2. Medical Image Segmentation Techniques; 2.1. Histogram-Based Segmentation; 2.2. Region-Based Segmentation; 2.3. Split-and-Merge Segmentation; 2.4. Edge-Based Segmentation; 3. Metaheuristics; 3.1. Genetic Algorithm; 3.2. Particle Swarm Optimization; 3.3. Ant Colony Optimization; 3.4. Bat Optimization Algorithm; 4. Segmentation Algorithms for Medical Images
  • 4.1. Metaheuristics-Based Segmentation of Magnetic Resonance Images4.2. Metaheuristics Based Segmentation of Computed Tomography Images; 5. Conclusion; References; Chapter 2: Automated Pathology Image Analysis; 1. Introduction; 2. Need for Quantitative Image Analysis in Pathology; 2.1. Differences in Radiology and Histopathology Automated Techniques; 2.2. Anomalies in Microscopic Images; 3. Histology-Imaging Technologies; 3.1. Light Microscopy; 3.2. Fluorescence Microscopy; 3.3. Confocal Microscopy; 3.4. Hyperspectral and Multispectral Microscopy; 3.5. Electron Microscopy
  • 3.6. Transmission Electron Microscopes3.7. Scanning Electron Microscopes; 4. Automated Pathology Image Analysis; 4.1. Image Preprocessing; 4.1.1. Color Illumination and Normalization; 4.1.2. Image Enhancement; 4.2. Image Segmentation; 4.2.1. Pathology Image Segmentation; 4.3. Feature Extraction; 4.3.1. Pixel-Level Features; 4.3.2. Object-Level Features; 4.3.3. Semantic-Level Features; 4.4. Feature Selection; 4.4.1. Dimensionality Reduction; 4.5. Image Classification; 5. Pathology Image Data Sources; 5.1. The Cancer Genome Atlas; 5.2. Lung Image Database Consortium
  • 5.3. National Biomedical Imaging Archive (NBIA)5.4. Microscopic Blood Cell Image Dataset (ALL-IDB1, ALL-IDB2); 5.5. DTI Database; 6. Discussion; 7. Future Trends and Open Issues; References; Chapter 3: Multiple Kernel-Learning Approach for Medical Image Analysis; 1. Introduction; 2. Related Literature; 3. Nature and Characteristics of Biomedical Images; 3.1. Image Characteristics; 3.2. Medical Imaging Modalities; 3.3. Image Noise; 4. Feature Extraction and Image Descriptors; 4.1. Image Descriptors; 5. Computer-Aided Diagnosis; 6. Kernel-Based Machine Learning; 6.1. Basics in Machine Learning
  • 6.1.1. Classification and Regression6.1.2. Cost Function; 6.2. Similarity Measures and Features; 6.3. Kernels; 6.4. Kernel Trick; 6.5. Kernel Matrix; 7. Multiple Kernel-Learning Model; 7.1. 1-Norm Soft-Margin SVM; 7.2. MKL Optimization Using SDP; 8. Multiple Kernel Learning for Biomedical Image Analysis; 8.1. Open-Source Computer Vision; 8.2. Shogun Machine-Learning Toolbox; 8.3. Case Study; 8.3.1. Dataset; 8.3.2. Experiment; 9. Discussion; 9.1. Limitations; 9.2. Future Challenges; 10. Conclusion; Acknowledgments; References; Further Reading; Section B: Medical Image Enhancement
Control code
SCIDI1020172347
Dimensions
unknown
Edition
First edition.
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9780128131749
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
Online access with subscription: Elsevier (Sciencedirect Freedom Collection)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1020172347
  • (OCoLC)1020172347

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