Computational Analysis for Digital Medical Imagery

1. Auflage 2026
ISBN: 978-1-041-21404-5
Verlag: Taylor & Francis Ltd

Buch, Englisch, 328 Seiten, Format (B × H): 156 mm x 234 mm

Advanced computational techniques and intelligent algorithms are now being used for processing, analyzing, and interpreting medical images across diverse healthcare applications. It integrates image processing, machine learning, deep learning, and computer vision to enhance diagnostic accuracy, disease detection, and clinical decision-making. Its potential lies in enabling faster, automated, and more precise medical assessments while supporting personalized and data-driven healthcare systems. The field also drives innovation in radiology, telemedicine, surgical planning, and smart healthcare technologies, making it a critical area of modern biomedical research and practice.

The book delves into the latest computational methodologies and artificial intelligence techniques used in the analysis, interpretation, and enhancement of digital medical images. It aims to cover a wide array of topics, from foundational imaging techniques to advanced Al-driven models, including machine learning, deep learning, and neural networks applied in medical imaging. It also addresses critical aspects such as data preprocessing, feature extraction, segmentation, and diagnostic interpretation, offering insights into how computational applies are revolutionizing clinical decision-making, diagnostic accuracy, and patient outcomes.

This book is designed for researchers and professionals in medical imaging, artificial intelligence, biomedical engineering, and healthcare. It is also useful for clinicians and industry practitioners applying computational techniques to improve diagnostic decision-making.

Zielgruppe

Academic, Postgraduate, and Professional Practice & Development

Autoren/Hrsg.

Kumar Rai, Bipin

Dwivedi, Anshu Kumar

Tran, Duc-Tan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

Preface. Section I: Foundations of Medical Imaging. 1. Introduction to Computational Analysis in Medical Imaging.  2. Foundation of Digital Medical Imaging Technologies. 3. Feature Extraction and Selection in Medical Imaging. 4. Segmentation Techniques in Medical Imaging. Section II: Machine Learning and Deep Learning in Medical Imaging. 5. Medical Image Classification using Machine Learning Artificial Neural Networks (ANN). 6. Machine Learning Medical Image Classification and Detection Data Analysis. 7. Alzheimer’s Disease Prediction Model using Deep Learning Convolutional Neural Network (CNN). 8. Data-Driven Enhancement and Model Validation for Clinical Heart Attack Prediction. 9. Lightweight Optimization Strategies for Medical Neural Networks. Section III: Advanced AI-Driven Imaging Systems. 10. AI-Assisted 3D Reconstruction of Organs from 2D Medical Slices: Segmentation Strategies and Volume-Based Visualization. 11. Application of Natural Language Processing in Medical Imaging. 12. AI-Driven Image Registration and Fusion for Multi-Modal Imaging. 13. Explainability and Interpretability in Medical Image Analysis. Section IV: Secure and Emerging Healthcare AI Applications. 14. Applications of Blockchain and Federated Learning for Secure Medical Imaging. 15. Evaluating the Freshness of Meat based on Electrical Impedance Spectroscopy (EIS) Technology.

Über Autor(innen)

Dr. Bipin Kumar Rai is a Professor in the Department of Computer Science & Engineering, at Dayananda Sagar University, India. He holds a PhD from Banasthali Vidyapith, along with M.Tech and B.Tech degrees in Computer Science and Engineering. Dr. Rai has over 21 years of teaching experience at renowned institutions. His areas of interest include cryptography and information security, machine learning, and blockchain technology. He has published over 70 research papers in WoS/Scopus-indexed journals, conferences, and book chapters, and has authored/edited 7 books with reputable publishers like Wiley/Springer/T&F Group. He has served as a Guest Editor and Reviewer for several WoS/Scopus-indexed journals. He has also served as a session chair, reviewer, and presenter at numerous conferences, workshops, and symposiums.

Dr. Rai has held various administrative roles, including Dean of Academics and Head of Department for NBA-accredited program. He has expertise in implementing Outcome-Based Education (OBE), which is essential for NBA/NAAC accreditation processes. Dr. Rai is actively engaged in professional development and is an esteemed member of professional bodies such as the Senior Member of IEEE, Computer Society of India (CSI), Indian Society for Technical Education (ISTE), and Association for Computing Machinery (ACM).

Dr. Anshu Kumar Dwivedi has a background in Computer Science and Engineering. He is a senior member of IEEE. He is an assistant professor at School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India. He has a PhD in Computer Science and Engineering from Madan Mohan Malaviya University of Technology, Gorakhpur on a regular basis and MTech (Hons) in Computer Engineering from YMCA University of Science and Technology, Faridabad. He has a Bachelor of Technology from UPTU, Lucknow. Dr. Dwivedi also cleared GATE 2010, and 2018. He brings over 12+ years of teaching and research expertise. Dr. Dwivedi boasts a prolific research background with more than 35 plus research publications published in esteemed journals, Dr. Dwivedi is a senior member of the IEEE, AIENG, and CSI. Dr. Dwivedi has authored a book Theory of Automata and Formal Languages (2015), and Healthcare Systems and Health Informatics Using Internet of Things (2022). Dr. Dwivedi is a dedicated academician and researcher who has made notable contributions in the field of Computer Science and Engineering.

Duc-Tan Tran is a Professor and Vice Dean at the Faculty of Electrical and Electronic Engineering at Phenikaa University, Hanoi, Vietnam. Prior to joining Phenikaa University, Dr. Tan was an Associate Professor at the Faculty of Electronics and Telecommunication, VNU University of Engineering and Technology. He also served as the Vice Dean of the faculty from 2016 to 2019. He has published over 150 research papers and has been awarded the "Best Paper Award" at the 9th International Conference on Multimedia and Ubiquitous Engineering (MUE-15) and the International Conference on Green and Human Information Technology (ICGHIT-2015). In 2008, he was recognized as an excellent young researcher by Vietnam National University, Hanoi, and was awarded the third prize in the "Vietnamese Talents" contest. His primary research interests include the representation, processing, analysis, and communication of information embedded in signals and datasets. Tran actively participates in international conferences and journals by serving as a TP Co-chair, technical committee program member, track chair, session chair, and reviewer.