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Cardiovascular and Coronary Artery Imaging
Volume 1
- 1st Edition - November 24, 2021
- Editors: Ayman S. El-Baz, Jasjit S. Suri
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 7 0 6 - 0
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 7 0 7 - 7
Cardiovascular and Coronary Artery Imaging, Volume One covers state-of-the-art approaches for automated non-invasive systems in early cardiovascular disease diagnosis. The book i… Read more
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Request a sales quoteCardiovascular and Coronary Artery Imaging, Volume One covers state-of-the-art approaches for automated non-invasive systems in early cardiovascular disease diagnosis. The book includes several prominent imaging modalities, such as MRI, CT and PET technologies. A special emphasis is placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. This is a comprehensive, multi-contributed reference work that details the latest developments in spatial, temporal and functional cardiac imaging.
- Takes an integrated approach to cardiovascular and coronary imaging, covering machine learning, deep learning and reinforcement learning approaches
- Covers state-of-the-art approaches for automated non-invasive systems for early cardiovascular disease diagnosis
- Provides a perspective on future cardiovascular imaging and highlights areas that still need improvement
Researchers in medical imaging, cardiovascular imaging, radiologists. Clinicians
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Chapter 1. Advanced coronary artery imaging: optical coherence tomography
- Abstract
- 1.1 Introduction
- 1.2 Basic principles of light
- 1.3 Mechanism and technical modalities of OCT
- 1.4 Scanning techniques
- 1.5 Pullback
- 1.6 Image interpretation
- 1.7 Image artifact
- 1.8 Clinical applications
- 1.9 Safety and complications
- 1.10 Innovations of OCT
- 1.11 Clinical trials
- References
- Chapter 2. Technique of cardiac magnetic resonance imaging
- Abstract
- 2.1 Introduction
- 2.2 Physical principles and pulse sequences
- References
- Chapter 3. The role of automated 12-lead ECG interpretation in the diagnosis and risk stratification of cardiovascular disease
- Abstract
- 3.1 Introduction
- 3.2 Basic knowledge of ECG physiology
- 3.3 The 12-lead ECG
- 3.4 ECG signal processing
- 3.5 Cardiovascular diseases diagnosed by the 12-lead ECG
- 3.6 Automated ECG interpretation
- 3.7 “Logic” used in automated ECG interpretation systems
- 3.8 Machine learning and automated 12-lead ECG analysis
- 3.9 Basic principles of risk stratification
- 3.10 ECG-derived markers for risk stratification
- 3.11 Challenges and opportunities
- References
- Chapter 4. Extracting heterogeneous vessels in X-ray coronary angiography via machine learning
- Abstract
- 4.1 Introduction
- 4.2 Related works
- 4.3 MCR-RPCA: motion coherency regularized RPCA for vessel extraction
- 4.4 SVS-net: sequential vessel segmentation via channel attention network
- 4.5 VRBC-t-TNN: accurate heterogeneous vessel extraction via tensor completion of X-ray coronary angiography backgrounds
- 4.6 Conclusion
- Acknowledgments
- References
- Chapter 5. Assessing coronary artery disease using coronary computed tomography angiography
- Abstract
- 5.1 Introduction
- 5.2 Patient selection
- 5.3 Spatial resolution
- 5.4 Temporal resolution
- 5.5 Technical issues in specific patient subgroups
- 5.6 Clinical trials comparing CCTA to other modalities
- 5.7 Conclusion
- References
- Chapter 6. Multimodality noninvasive cardiovascular imaging for the evaluation of coronary artery disease
- Abstract
- 6.1 Introduction
- 6.2 Ischemic cascade
- 6.3 Exercise stress echocardiography
- 6.4 Pharmacologic stress echocardiography
- 6.5 Myocardial perfusion stress echocardiography
- 6.6 Left ventricular strain in exercise stress echocardiography
- 6.7 Limitations of stress echocardiography
- 6.8 Computed tomography coronary calcium score
- 6.9 Limitations of coronary artery calcium
- 6.10 Computed tomography coronary angiogram
- 6.11 Limitations of computed tomography coronary angiogram
- 6.12 Computed tomography in combination with single-photon emission tomography
- 6.13 Computed tomography in combination with positron emitting tomography
- 6.14 Limitations and strengths of positron emission tomography and SPECT imaging
- 6.15 CTCA and fractional flow reserve
- 6.16 Limitations of FFR CCTA
- 6.17 Cardiac magnetic resonance angiography
- 6.18 Conclusion
- References
- Chapter 7. Magnetic resonance imaging of ischemic heart disease
- Abstract
- 7.1 Introduction
- 7.2 Cardiac MR imaging of myocardial infarction
- 7.3 MR indicators of myocardial infraction severity
- 7.4 Myocardial infarction complications
- 7.5 Future directions
- References
- Chapter 8. CT angiography of anomalous pulmonary veins
- Abstract
- 8.1 Introduction
- 8.2 Classification
- 8.3 Anomalous in caliber of pulmonary veins
- 8.4 Total anomalous pulmonary venous return
- 8.5 Partial anomalous pulmonary venous return
- 8.6 Merits, limitations, and future directions
- 8.7 Conclusion
- References
- Further reading
- Chapter 9. Machine learning to predict mortality risk in coronary artery bypass surgery
- Abstract
- 9.1 Introduction
- 9.2 Principles and applications of machine learning
- 9.3 Conclusion
- References
- Chapter 10. Computed tomography angiography of congenital anomalies of pulmonary artery
- Abstract
- 10.1 Introduction
- 10.2 Classification
- 10.3 Merits, limitations, and future directions
- 10.4 Conclusion
- References
- Chapter 11. Obstructive coronary artery disease diagnostics: machine learning approach for an effective preselection of patients
- Abstract
- 11.1 Introduction
- 11.2 In search for additional diagnostic information
- 11.3 Materials and methods
- 11.4 Results
- 11.5 Conclusions
- References
- Chapter 12. Heart disease prediction using convolutional neural network
- Abstract
- 12.1 Introduction
- 12.2 Materials
- 12.3 Methods
- 12.4 Conclusion/summary
- Acknowledgments
- Author contribution
- Conflict of interest
- References
- Chapter 13. Gene polymorphism and the risk of coronary artery disease
- Abstract
- 13.1 Introduction
- 13.2 Methodology
- 13.3 Results
- 13.4 Discussion
- 13.5 Conclusion
- References
- Chapter 14. Role of optical coherence tomography in borderline coronary lesions
- Abstract
- 14.1 Introduction
- 14.2 Physics of optical coherence tomography
- 14.3 Imaging technique
- 14.4 Optical coherence tomography image
- 14.5 Optical coherence tomography versus intravascular ultrasound
- 14.6 Optical coherence tomography in borderline lesions
- 14.7 Conclusion
- References
- Index
- No. of pages: 358
- Language: English
- Edition: 1
- Published: November 24, 2021
- Imprint: Academic Press
- Paperback ISBN: 9780128227060
- eBook ISBN: 9780128227077
AS
Ayman S. El-Baz
Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master’s degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents).
Affiliations and expertise
University of Louisville, USAJS
Jasjit S. Suri
Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.
Affiliations and expertise
Chairman, AtheroPoint LLC, USARead Cardiovascular and Coronary Artery Imaging on ScienceDirect