Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

by Nilanjan Dey
Released July 2019
Publisher(s): Academic Press
ISBN: 9780128180051

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Book description

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.

  • Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges
  • Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications
  • Introduces several techniques for medical image processing and analysis for CAD systems design

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Preface
  7. Chapter 1: Classification of unhealthy and healthy neonates in neonatal intensive care units using medical thermography processing and artificial neural network
    1. Abstract
    2. Acknowledgment
    3. 1.1 Introduction
    4. 1.2 Methods
    5. 1.3 Experiments and results
    6. 1.4 Conclusion
  8. Chapter 2: Use of health-related indices and classification methods in medical data
    1. Abstract
    2. 2.1 Introduction
    3. 2.2 Health indices
    4. 2.3 Medical data classification methods
    5. 2.4 Applications and evaluation of classification methods
    6. 2.5 Comparison
    7. 2.6 Conclusions
  9. Chapter 3: Image analysis for diagnosis and early detection of hepatoprotective activity
    1. Abstract
    2. 3.1 Introduction
    3. 3.2 Literature survey
    4. 3.3 Materials and methods
    5. 3.4 Conclusion
  10. Chapter 4: Characterization of stuttering dysfluencies using distinctive prosodic and source features
    1. Abstract
    2. 4.1 Introduction
    3. 4.2 Relevance of prosodic and source features
    4. 4.3 Extraction of prosodic and source features
    5. 4.4 Evaluation of prosodic and source features for characterizing dysfluencies
    6. 4.5 Conclusions
  11. Chapter 5: A deep learning approach for patch-based disease diagnosis from microscopic images
    1. Abstract
    2. 5.1 Introduction
    3. 5.2 Related works
    4. 5.3 Proposed work
    5. 5.4 Experimental results and analysis
    6. 5.5 Conclusion
  12. Chapter 6: A breast tissue characterization framework using PCA and weighted score fusion of neural network classifiers
    1. Abstract
    2. Conflicts of interest
    3. 6.1 Introduction
    4. 6.2 Materials and methods
    5. 6.3 Experiments and analysis of results
    6. 6.4 Discussion
    7. 6.5 Conclusion
  13. Chapter 7: Automated arrhythmia classification for monitoring cardiac patients using machine learning techniques
    1. Abstract
    2. 7.1 Introduction
    3. 7.2 Literature survey
    4. 7.3 Methodology
    5. 7.4 Dimensionality reduction
    6. 7.5 Classification
    7. 7.6 Evaluation metrics
    8. 7.7 Implications
    9. 7.8 Generalization capability of the proposed arrhythmia classifier
    10. 7.9 Conclusion
  14. Chapter 8: IOT-based fluid and heartbeat monitoring for advanced healthcare
    1. Abstract
    2. 8.1 Introduction
    3. 8.2 Medical health care paradigm
    4. 8.3 Data fusion models and algorithms
    5. 8.4 Literature survey
    6. 8.5 Proposed methodology
    7. 8.6 Data flow diagram
    8. 8.7 Heart beat monitoring
    9. 8.8 Experimental setup
    10. 8.9 Results and discussion
    11. 8.10 Conclusion
  15. Index

Product information

  • Title: Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis
  • Author(s): Nilanjan Dey
  • Release date: July 2019
  • Publisher(s): Academic Press
  • ISBN: 9780128180051