Cover for Advanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis

A volume in Hybrid Computational Intelligence for Pattern Analysis and Understanding

Book2020

Edited by:

Tapan Gandhi, Siddhartha Bhattacharyya, ... Sandip Dey

Advanced Machine Vision Paradigms for Medical Image Analysis

A volume in Hybrid Computational Intelligence for Pattern Analysis and Understanding

Book2020

 

Cover for Advanced Machine Vision Paradigms for Medical Image Analysis

Edited by:

Tapan Gandhi, Siddhartha Bhattacharyya, ... Sandip Dey

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Book description

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, ... read full description

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Table of contents

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  2. Book chapterAbstract only

    Chapter 1 - An introductory illustration of medical image analysis

    Sandip Dey, Debanjan Konar, ... Siddhartha Bhattacharyya

    Pages 1-9

  3. Book chapterAbstract only

    Chapter 2 - Computer-aided decision support system for symmetry-based prenatal congenital heart defects

    S. Sridevi, Shanmugakumar Murugesan, ... D. Kavitha

    Pages 11-53

  4. Book chapterAbstract only

    Chapter 3 - Morphological extreme learning machines applied to the detection and classification of mammary lesions

    Washington Wagner Azevedo da Silva, Maíra Araújo de Santana, ... Wellington Pinheiro dos Santos

    Pages 55-95

  5. Book chapterAbstract only

    Chapter 4 - 4D medical image analysis: a systematic study on applications, challenges, and future research directions

    E. Grace Mary Kanaga, J. Anitha and D. Sujitha Juliet

    Pages 97-130

  6. Book chapterAbstract only

    Chapter 5 - Comparative analysis of hybrid fusion algorithms using neurocysticercosis, neoplastic, Alzheimer's, and astrocytoma disease affected multimodality medical images

    B. Rajalingam, R. Priya and R. Bhavani

    Pages 131-167

  7. Book chapterAbstract only

    Chapter 6 - Binary descriptor design for the automatic detection of coronary arteries using metaheuristics

    Ivan Cruz-Aceves, Fernando Cervantes-Sanchez, ... Sergio Solorio-Meza

    Pages 169-188

  8. Book chapterAbstract only

    Chapter 7 - A cognitive perception on content-based image retrieval using an advanced soft computing paradigm

    K. Martin Sagayam, P. Malin Bruntha, ... Omer Deperlioglu

    Pages 189-211

  9. Book chapterAbstract only

    Chapter 8 - Early detection of Parkinson's disease using data mining techniques from multimodal clinical data

    Sneham Priya, R. Priyatharshini, ... R. Sai Swarna

    Pages 213-228

  10. Book chapterAbstract only

    Chapter 9 - Contrast improvement of medical images using advanced fuzzy logic-based technique

    Dibya Jyoti Bora

    Pages 229-257

  11. Book chapterAbstract only

    Chapter 10 - Bone age assessment using metric learning on small dataset of hand radiographs

    Shipra Madan, Tapan Kumar Gandhi and Santanu Chaudhury

    Pages 259-271

  12. Book chapterNo access

    Chapter 11 - Conclusion and future research directions

    Sandip Dey, Debanjan Konar, ... Siddhartha Bhattacharyya

    Pages 273-277

  13. Book chapterNo access

    Index

    Pages 279-289

About the book

Description

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated.

Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs.

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated.

Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs.

Key Features

  • Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence
  • Highlights the advancement of conventional approaches in the field of medical image processing
  • Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
  • Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence
  • Highlights the advancement of conventional approaches in the field of medical image processing
  • Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis

Details

ISBN

978-0-12-819295-5

Language

English

Published

2020

Copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Imprint

Academic Press

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Editors

Tapan Gandhi

Siddhartha Bhattacharyya

Sourav De

Debanjan Konar

Sandip Dey