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Advances in Artificial Intelligence
Biomedical Engineering Applications in Signals and Imaging
- 1st Edition - May 21, 2024
- Editors: Kunal Pal, Bala Chakravarthy Neelapu, J. Sivaraman
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 9 0 7 3 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 3 9 2 - 1
Artificial intelligence in healthcare has become one of the best assisting techniques for clinicians in proper diagnosis and surgery. In biomedical applications, artificial… Read more
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Request a sales quoteArtificial intelligence in healthcare has become one of the best assisting techniques for clinicians in proper diagnosis and surgery. In biomedical applications, artificial intelligence algorithms are explored for bio-signals, such as electrocardiogram (ECG/EKG), electrooculogram (EOG), electromyogram (EMG), electroencephalogram (EEG), blood pressure, heart rate, and nerve conduction, and for bio-imaging modalities, such as computed tomography (CT), cone-beam computed tomography (CBCT), and MRI (magnetic resonance imaging). Advancements in artificial intelligence and big data have increased the development of innovative medical devices in healthcare applications. Advances in Artificial Intelligence: Biomedical Engineering Applications in Signals and Imaging provides an overview of artificial intelligence in biomedical applications, including both bio-signals and bio-imaging modalities. The chapters contain a mathematical formulation of algorithms and their applications in the biomedical eld, including case studies. Biomedical engineers, advanced students, and researchers can use this book to apply their knowledge in artificial intelligence-based processes to biological signals, implement mathematical models and advanced algorithms, and develop AI-based medical devices.
- Covers the recent advancements of artificial intelligence in healthcare, including case studies on how this technology can be used
- Provides an understanding of the design of experiments to validate the developed algorithms
- Presents an understanding of the versatile application of artificial intelligence in bio-signal and bio-image processing techniques
Researchers, experts, masters and PhD students in the fields of biomedical engineering, computer science and engineering, electronics engineering. Scientists and researchers working in the field of biosignal processing, biomedical Image Processing, Artificial Intelligence in biomedical applications
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Chapter 1 Introduction to biomedical signals and biomedical imaging
- Abstract
- 1 The purpose of analysis of biosignals and medical images using artificial intelligence
- 2 Classification of biomedical signals and images for AI-enabled diagnosis
- 3 Electrical signals
- 4 Magnetic signals
- 5 Optical and thermal signals
- 6 Mechanical signals
- 7 Acoustic signals
- 8 Ophthalmoscopic images
- 9 X-ray images
- 10 MRI images
- 11 Nuclear medicine images
- 12 Ultrasonic images
- References
- Chapter 2 Medical applications of artificial intelligence
- Abstract
- 1 Introduction
- 2 Evolution of AI in medicine
- 3 Recent application of AI in medicine
- 4 Limitations, challenges, and future scope
- 5 Conclusions
- References
- Chapter 3 Decipher the mask-induced cardiac changes in the ECG signals using DWT and machine learning classifiers
- Abstract
- 1 Introduction
- 2 Materials and methods
- 3 Results
- 4 Discussions
- 5 Limitations, future scope, and conclusion
- References
- Chapter 4 A robust to noise classification method for the heart sound signals using deep learning technique
- Abstract
- Acknowledgment
- 1 Introduction
- 2 Literature survey
- 3 Proposed methodology
- 4 Experimental results
- 5 Conclusion and future works
- References
- Chapter 5 A hybrid ResNet-18-UNet model for MRI brain tumor segmentation
- Abstract
- 1 Introduction
- 2 Literature review
- 3 Proposed method
- 4 Results
- 5 Discussion
- 6 Conclusion
- References
- Chapter 6 Artificial intelligence (AI) in medical robotics
- Abstract
- 1 Introduction
- 2 Artificial intelligence in healthcare
- 3 AI in robot-assisted surgery
- 4 AI in medical devices
- 5 Limitations
- 6 Conclusion
- References
- Chapter 7 Artificial intelligence in medical education
- Abstract
- 1 An overview of AI
- 2 Medical preparation for AI
- 3 Internet of things adoption in technology
- 4 Intelligent swarms in education
- 5 AI in education evaluation
- 6 Role of AI in medical healthcare education
- 7 Conclusion
- References
- Chapter 8 Artificial intelligence-based obstructive sleep apnea detection using ECG signals
- Abstract
- 1 Introduction
- 2 Understanding OSA
- 3 Automatic diagnosis
- 4 Databases
- 5 Recent advances in automated OSA diagnosis using single-lead ECG signals
- 6 Conclusion
- References
- Chapter 9 Artificial intelligence techniques for diagnosis of atrial fibrillation
- Abstract
- 1 What is AF?
- 2 AF in India and worldwide
- 3 Significance of artificial intelligence in AF
- 4 Risks associated with AF
- 5 AF management
- 6 Primary prevention of AF
- 7 Summary
- References
- Chapter 10 Artificial intelligence in monitoring and correction of functional state based on electrocardiosignal
- Abstract
- Acknowledgments
- 1 Introduction
- 2 The cardiac signal and other signals processing using the structural method with variable resolution
- 3 Determining the physiological cost of a military serviceman’s activity in the field using innovative miniature devices: Different scenarios of use
- 4 The use of telemedicine systems with automatic processing and analysis of ECG and cardiac intervalogram signals to assess the functional state of medical doctors and nurses with intense mental and physical work
- 5 Conclusions
- References
- Chapter 11 Deep learning methods for drug repurposing through heterogeneous data
- Abstract
- 1 Introduction
- 2 Evaluation of state-of-the-art approaches
- 3 Conclusions
- References
- Chapter 12 Explainable AI for medical applications
- Abstract
- 1 Introduction
- 2 Basics of XAI
- 3 Challenges in medical applications
- 4 XAI techniques for medical applications
- 5 Applications of XAI in medical imaging
- 6 Future directions in XAI for medical applications
- 7 Conclusion
- References
- Chapter 13 Artificial intelligence-based smart devices for biomedical applications
- Abstract
- 1 Introduction
- 2 Overview of AI
- 3 Bibliometric analysis on the role of AI in biomedical applications
- 4 Architecture and applications of extensively used AI models
- 5 Conclusion
- References
- Chapter 14 Automation in orthodontics and orthopedics using artificial intelligence
- Abstract
- 1 Introduction
- 2 Orthodontics
- 3 AI in orthodontics
- 4 Orthopedics
- 5 Challenges and limitation of AI in orthopedics and orthodontics
- 6 Conclusion
- References
- Chapter 15 Data-driven model for healthcare diagnosis
- Abstract
- 1 Introduction to data-driven models
- 2 Traditional health diagnosis model
- 3 Role of data-driven models in healthcare diagnosis
- 4 Conclusion
- References
- Further reading
- Chapter 16 Artificial intelligence in diabetes management
- Abstract
- 1 Introduction
- 2 Data collection and integration
- 3 ML techniques for diabetes risk prediction
- 4 AI in blood glucose monitoring
- 5 Personalized diabetes management
- 6 AI in diabetic complication detection
- 7 Ethical considerations and challenges
- 8 Future directions and conclusion
- References
- Chapter 17 2D and 3D segmentation of organs using artificial intelligence
- Abstract
- 1 Introduction
- 2 Datasets
- 3 Approaches
- 4 Challenges and limitations
- 5 Conclusions
- References
- Chapter 18 Early-stage identification of autism in children using gesture monitoring based on artificial intelligence
- Abstract
- 1 Introduction
- 2 Understanding ASD
- 3 Early detection of autism
- 4 Gesture monitoring and autism
- 5 AI in autism diagnosis
- 6 Data collection and ethical considerations
- 7 Development of gesture-based AI model
- 8 Evaluation and validation of the AI model
- 9 Implications and future directions
- References
- Chapter 19 Artificial intelligence in diagnosis of neural disorders using biosignals and imaging
- Abstract
- 1 Introduction
- 2 Signal and image modalities for neural disorders
- 3 Neural disorders detection using artificial intelligence
- 4 Discussion
- 5 Conclusion
- References
- Chapter 20 Biomedical image security
- Abstract
- 1 Introduction
- 2 Background of medical image security
- 3 Methods of medical image security
- 4 Performance metrics
- 5 Conclusion
- References
- Index
- No. of pages: 630
- Language: English
- Edition: 1
- Published: May 21, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443190735
- eBook ISBN: 9780443153921
KP
Kunal Pal
Dr. Kunal Pal is a Professor in the Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, India. His major research interests revolve around biomedical signal processing, biomedical equipment design, soft materials, and controlled drug delivery. He has published more than 100 publications in SCI-cited journals of high repute.
Affiliations and expertise
Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, Odisha, India.BN
Bala Chakravarthy Neelapu
Dr. Bala Chakravarthy Neelapu has completed B.Tech in Electronics and Communication Engineering Dr. Bala Chakravarthy Neelapu is working as an assistant professor in the Department of Biotechnology and Medical Engineering at the National Institute of Technology, Rourkela, India. His area of interest is medical image processing and computer vision. He has authored more than 20 articles in SCI-indexed journals. JNTU Hyderabad in 2008, M.Tech. in Electronics and Communication Engineering from JNTU Kakinada, in 2011, and PhD in Engineering from AcSIR (Academy of Scientific and Innovative Research) at CSIR-Central Scientific Instruments Organization, Chandigarh in 2018. Currently, he is working as Assistant Professor in the Department of Biotechnology and Medical Engineering of National Institute of Technology Rourkela, India. Prior to join NIT Rourkela, he had worked as Assistant Professor at K L University, Andhra Pradesh. His area of interest is Medical Image Processing and Computer Vision. He has authored more than 10 articles in SCI indexed journals and conferences. Dr. Bala Chakravarthy has filed 2 patents in India and US and 1 of them was granted by US Patent Office. He has served as a Guest Editor of 2 reputed SCI journals and also served as a reviewer of several SCI and SCOPUS indexed journals.
Affiliations and expertise
Assistant Professor, Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, IndiaJS
J. Sivaraman
Dr. J. Sivaraman is working as an assistant professor and principal investigator of Bio-signals and Medical Instrumentation Laboratory in the Department of Biotechnology and Medical Engineering at the National Institute of Technology, Rourkela, India. His research interests include electrocardiography, ECG signal analysis and processing, atrial arrhythmias such as atrial brillation, and signal processing for bioelectric measurements. He has authored more than 40 articles in SCI-indexed journals, conferences, and book chapters
Affiliations and expertise
Assistant Professor and Principal Investigator of Bio-signals and Medical Instrumentation Laboratory, Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, IndiaRead Advances in Artificial Intelligence on ScienceDirect