Disruptive Trends in Computer Aided Diagnosis
1st Edition
Published on 29. September 2021
Book
Hardback
196 pages
978-0-367-49337-0 (ISBN)
Description
Disruptive Trends in Computer Aided Diagnosis collates novel techniques and methodologies in the domain of content based image classification and deep learning/machine learning techniques to design efficient computer aided diagnosis architecture. It is aimed to highlight new challenges and probable solutions in the domain of computer aided diagnosis to leverage balancing of sustainable ecology.
The volume focuses on designing efficient algorithms for proposing CAD systems to mitigate the challenges of critical illnesses at an early stage. State-of-the-art novel methods are explored for envisaging automated diagnosis systems thereby overriding the limitations due to lack of training data, sample annotation, region of interest identification, proper segmentation and so on. The assorted techniques addresses the challenges encountered in existing systems thereby facilitating accurate patient healthcare and diagnosis.
Features:
An integrated interdisciplinary approach to address complex computer aided diagnosis problems and limitations.
Elucidates a rich summary of the state-of-the-art tools and techniques related to automated detection and diagnosis of life threatening diseases including pandemics.
Machine learning and deep learning methodologies on evolving accurate and precise early detection and medical diagnosis systems.
Information presented in an accessible way for students, researchers and medical practitioners.
The volume would come to the benefit of both post-graduate students and aspiring researchers in the field of medical informatics, computer science and electronics and communication engineering. In addition, the volume is also intended to serve as a guiding factor for the medical practitioners and radiologists in accurate diagnosis of diseases.
The volume focuses on designing efficient algorithms for proposing CAD systems to mitigate the challenges of critical illnesses at an early stage. State-of-the-art novel methods are explored for envisaging automated diagnosis systems thereby overriding the limitations due to lack of training data, sample annotation, region of interest identification, proper segmentation and so on. The assorted techniques addresses the challenges encountered in existing systems thereby facilitating accurate patient healthcare and diagnosis.
Features:
An integrated interdisciplinary approach to address complex computer aided diagnosis problems and limitations.
Elucidates a rich summary of the state-of-the-art tools and techniques related to automated detection and diagnosis of life threatening diseases including pandemics.
Machine learning and deep learning methodologies on evolving accurate and precise early detection and medical diagnosis systems.
Information presented in an accessible way for students, researchers and medical practitioners.
The volume would come to the benefit of both post-graduate students and aspiring researchers in the field of medical informatics, computer science and electronics and communication engineering. In addition, the volume is also intended to serve as a guiding factor for the medical practitioners and radiologists in accurate diagnosis of diseases.
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Academic, Postgraduate, Professional, and Undergraduate Advanced
Illustrations
8 s/w Photographien bzw. Rasterbilder, 50 s/w Zeichnungen, 25 s/w Tabellen, 58 s/w Abbildungen
25 Tables, black and white; 50 Line drawings, black and white; 8 Halftones, black and white; 58 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 17 mm
Weight
499 gr
ISBN-13
978-0-367-49337-0 (9780367493370)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Rik Das | Sudarshan Nandy | Siddhartha Bhattacharyya
Disruptive Trends in Computer Aided Diagnosis
Book
10/2024
1st Edition
Chapman & Hall/CRC
€67.90
Shipment within 15-20 days
Rik Das | Sudarshan Nandy | Siddhartha Bhattacharyya
Disruptive Trends in Computer Aided Diagnosis
E-Book
09/2021
1st Edition
Chapman & Hall/CRC
€61.99
Available for download
Rik Das | Sudarshan Nandy | Siddhartha Bhattacharyya
Disruptive Trends in Computer Aided Diagnosis
E-Book
09/2021
1st Edition
Chapman & Hall/CRC
€61.99
Available for download
Persons
Dr. Rik Das is an Assistant Professor for Post Graduate Programme in Information Technology, Xavier Institute of Social Service, Ranchi. Dr. Das has over 16 years of experience in academia and research with various leading Universities and Institutes in India including Narsee Monjee Institute of Management Studies (NMIMS) (Deemed-to-be-University), Globsyn Business School, Maulana Abul Kalam Azad University of Technology and so on. He has an early career stint in Business Development and Project Marketing with Industries like Great Eastern Impex Pvt. Ltd., Zenith Computers Ltd. and so on. Dr. Rik Das is appointed as a "Distinguished Speaker" by the "Association of Computing Machinery (ACM)", New York, USA in July, 2020. He is featured in uLektz Wall of Fame as one of the "Top 50 Tech Savvy Academicians in Higher Education across India" for the year 2019. He is also a Member of International Advisory Committee of AI-Forum, UK. Dr. Das is awarded with "Professional Membership" of the "Association of Computing Machinery (ACM)", New York, USA for the year 2020-21. He is the recipient of prestigious "InSc Research Excellence Award" hosted in the year 2020. Dr. Das is conferred with Best Researcher Award at International Scientist Awards on Engineering, Science and Medicine for the year 2021.
Dr. Sudarshan Nandy was felicitated with a Ph.D in Engineering and Technology from Kalyani University in the year 2014. He has obtained his M.Tech in Computer Science and Engineering from West Bengal University of Technology in the year 2007 . He earned his B.E degree in computer science and Engineering from BPUT, Orissa in the year 2004. He is presently working in the rank of Assistant Professor at the Dept. of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University of Kolkata, India. His area of research includes Artificial Neural Network, metaheuristic algorithms, optimization, functional analysis, cloud computing. He has contributed in many research articles in various journals and conferences of repute. He is also a member of various professional society.
Dr. Siddhartha Bhattacharyya is serving as a Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. He served as the Principal of RCC Institute of Information Technology, Kolkata, India during 2017-2019. He is a co-author of 5 books and the co-editor of 72 books and has more than 300 research publications in international journals and conference proceedings to his credit. His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks and quantum computing. Dr. Bhattacharyya is a life fellow of Optical Society of India (OSI), India, life fellow of International Society of Research and Development (ISRD), UK, a fellow of Institution of Engineering and Technology (IET), UK, a fellow of Institute of Electronics and Telecommunication Engineers (IETE), India and a fellow of Institution of Engineers (IEI), India.
Dr. Sudarshan Nandy was felicitated with a Ph.D in Engineering and Technology from Kalyani University in the year 2014. He has obtained his M.Tech in Computer Science and Engineering from West Bengal University of Technology in the year 2007 . He earned his B.E degree in computer science and Engineering from BPUT, Orissa in the year 2004. He is presently working in the rank of Assistant Professor at the Dept. of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University of Kolkata, India. His area of research includes Artificial Neural Network, metaheuristic algorithms, optimization, functional analysis, cloud computing. He has contributed in many research articles in various journals and conferences of repute. He is also a member of various professional society.
Dr. Siddhartha Bhattacharyya is serving as a Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. He served as the Principal of RCC Institute of Information Technology, Kolkata, India during 2017-2019. He is a co-author of 5 books and the co-editor of 72 books and has more than 300 research publications in international journals and conference proceedings to his credit. His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks and quantum computing. Dr. Bhattacharyya is a life fellow of Optical Society of India (OSI), India, life fellow of International Society of Research and Development (ISRD), UK, a fellow of Institution of Engineering and Technology (IET), UK, a fellow of Institute of Electronics and Telecommunication Engineers (IETE), India and a fellow of Institution of Engineers (IEI), India.
Content
1. Evolution of Computer Aided Diagnosis: The Inception and Progress
2. Computer Aided Diagnosis for a Sustainable World
3. Applications of Computer Aided Diagnosis Techniques for a Sustainable World
4. Applications of Generative Adversarial Network on Computer Aided Diagnosis
5. A Critical Review of Machine Learning Techniques for Diagnosing the Corona Virus Disease (COVID- 19)
6. Cardiac Health Assessment Using ANN in Diabetic Population
7. Efficient, Accurate and Early Detection of Myocardial Infarction Using Machine Learning
8. Diagnostics and Decision Support for Cardiovascular System: A Tool Based on PPG Signature
9. ARIMA Prediction Model Based Forecasting for COVID- 19 Infected and Recovered Cases
10. Conclusion
2. Computer Aided Diagnosis for a Sustainable World
3. Applications of Computer Aided Diagnosis Techniques for a Sustainable World
4. Applications of Generative Adversarial Network on Computer Aided Diagnosis
5. A Critical Review of Machine Learning Techniques for Diagnosing the Corona Virus Disease (COVID- 19)
6. Cardiac Health Assessment Using ANN in Diabetic Population
7. Efficient, Accurate and Early Detection of Myocardial Infarction Using Machine Learning
8. Diagnostics and Decision Support for Cardiovascular System: A Tool Based on PPG Signature
9. ARIMA Prediction Model Based Forecasting for COVID- 19 Infected and Recovered Cases
10. Conclusion