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Advanced Machine Vision Paradigms for Medical Image Analysis - 1st Edition - ISBN: 9780128192955

Advanced Machine Vision Paradigms for Medical Image Analysis

1st Edition

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Editors: Tapan Gandhi Siddhartha Bhattacharyya Sourav De Debanjan Konar Sandip Dey
Paperback ISBN: 9780128192955
Imprint: Academic Press
Published Date: 26th August 2020
Page Count: 308
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Table of Contents

1. Computer Aided Decision Support System for symmetry based prenatal congenital heart defects
2. Morphological Extreme Learning Machines applied to the detection and classification of mammary lesions
3. 4D Medical Image Analysis: A Systematic Study on Applications, Challenges and Future Research Directions
4. Comparative Analysis of Hybrid Fusion Algorithms using Neurocysticercosis, Neoplastic, Alzheimer's and Astrocytoma Disease affected Multimodality Medical Images
5. Binary Descriptors Design for the Automatic Detection of Coronary Arteries using Metaheuristics
6. A Cognitive Perception on Content Based Image Retrieval using Advanced Soft Computing Paradigm
7. Early detection of Parkinson’s Disease Using Data Mining Techniques from Multi-Modal Clinical Data
8. Contrast Improvement of Medical Images Using Advanced Fuzzy Logic Based Technique
9. Intelligent Heart Disease Prediction On Physical and Mental Parameters: A ML Based IoT and Big Data Application & Analysis


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.

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

Readership

Researchers, professionals, and graduate students in computer science and engineering, bioinformatics, and electrical engineering


Details

No. of pages:
308
Language:
English
Copyright:
© Academic Press 2020
Published:
26th August 2020
Imprint:
Academic Press
Paperback ISBN:
9780128192955

Ratings and Reviews


About the Editors

Tapan Gandhi

Dr Tapan K Gandhi is currently working as Associate Professor in the Dept. of Electrical Engineering, and adjunct faculty in the School of Information Technology, Indian Institute of Technology Delhi. He is also research affiliate to MIT, USA. His research expertise spans from Computational Neuroscience, Brain imaging, Assistive Technology, Bio-medical Instrumentation, machine learning, Cognitive Computing to Artificial intelligence. He is serving as the Chairperson of Project Prakash charitable Trust, that helps in Restoration of Vision and providing education to visually impaired in India.

Affiliations and Expertise

Assistant Professor, Department of Electrical Engineering, Indian Institute of Technology, Delhi, India

Siddhartha Bhattacharyya

Siddhartha Bhattacharyya [FIEI (I), FIETE, LFOSI, SMIEEE, SMACM, SMIETI, MIET(UK)] is currently serving as a Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. With over 20 years of experience in academics, he has authored/edited more than 50 books and more than 250 research publications in international journals and conference proceedings. His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks and quantum computing.

Affiliations and Expertise

CHRIST University, Bangalore, India

Sourav De

Dr. Sourav De is currently an Associate Professor of Computer Science & Engineering Department in Cooch Behar Government Engineering College, West Bengal. He served as a reviewer in several International IEEE conferences, international editorial books and reputed international journals. His research interests include soft computing, pattern recognition, image processing, and data mining. Dr. De is a Senior member of IEEE and also member of ACM, Institute of Engineers (IEI), Computer Science Teachers Association (CSTA), Institute of Engineers and IAENG, Hong Kong. He is a life member of ISTE, India.

Affiliations and Expertise

Department of Computer Science and Engineering, Cooch Behar Government Engineering College, Cooch Behar, India

Debanjan Konar

Debanjan Konar is an Assistant Professor at the Department of Computer Science and Engineering at Sikkim Manipal Institute of Technology, India. He is pursuing PhD from Indian Institute of Technology, Delhi and about to submit the PhD thesis on Quantum Self-supervised Neural Network for Medical Image Segmentation. His research interests include quantum computing, deep learning, machine learning, and medical image segmentation. He has published several papers in these areas in leading journals and IEEE international conferences. He is also a reviewer for various international journals and conferences.

Affiliations and Expertise

Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Gangtok, Sikkim, India

Sandip Dey

Sandip Dey is currently serving as an Assistant Professor in the Department of Computer Science of Sukanta Mahavidyalaya, West Bengal, India. He has more than 16 years of experience in academics. He is a co-author of one book and the co-editor of two books. He has about 40 research publications in several internationally reputed journals, international edited books, and international IEEE and Springer conference proceedings to his credit. He served as a reviewer in various reputed international journals, international IEEE and Springer conferences, international editorial books. His research interests include quantum computing, soft computing, image processing, and pattern recognition.

Affiliations and Expertise

Assistant Professor, Department of Computer Science and Engineering, OmDayal Group of Institutions, Birshibpur, Howrah, India