Cardiovascular and Coronary Artery Imaging
Volume 2
- 1st Edition - November 22, 2022
- Imprint: Academic Press
- Editors: Ayman S. El-Baz, Jasjit S. Suri
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 1 9 8 3 - 6
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 7 0 5 - 3
Cardiovascular and Coronary Artery Imaging, Volume Two presents the basics of echocardiography, nuclear imaging and magnetic resonance imaging (MRI) and provides insights into t… Read more
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Request a sales quoteCardiovascular and Coronary Artery Imaging, Volume Two presents the basics of echocardiography, nuclear imaging and magnetic resonance imaging (MRI) and provides insights into their appropriate use. The book covers state-of-the-art approaches for automated non-invasive systems for early cardiovascular and coronary artery disease diagnosis. It includes several prominent imaging modalities such as MRI, CT and PET technologies. Other sections focus on major trends and challenges in this area and present the latest techniques for cardiovascular and coronary image analysis.
- Takes an integrated approach to cardiovascular and coronary imaging using 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
- Dedication
- List of Contributors
- About the editors
- Acknowledgments
- Chapter 1. Predictors of outcome in ST-segment elevation myocardial infarction
- Abstract
- 1.1 Clinical predictors
- 1.2 Brain natriuretic peptide
- 1.3 Differential white blood cell count
- References
- Chapter 2. ST-segment elevation myocardial infarction
- Abstract
- 2.1 Definition
- 2.2 Epidemiology of ST elevation myocardial infarction
- 2.3 Etiology
- 2.4 Pathophysiology
- 2.5 Management
- 2.6 Prevention
- 2.7 Complications
- 2.8 Prognosis
- 2.9 Conclusion
- References
- Chapter 3. The effect of patient-centered education in adherence to the treatment regimen in patients with coronary artery disease
- Abstract
- 3.1 Introduction
- 3.2 Methods
- 3.3 Findings
- 3.4 Discussion
- 3.5 Limitations
- 3.6 Conclusion
- References
- Chapter 4. Artificial intelligence in cardiovascular imaging
- Abstract
- 4.1 Introduction
- 4.2 Artificial intelligence
- 4.3 Cardiovascular imaging with machine learning
- 4.4 Cardiovascular imaging with deep learning
- 4.5 Discussion
- 4.6 Summary
- References
- Chapter 5. Valvular assessment and flow quantification
- Abstract
- 5.1 Introduction
- 5.2 Techniques
- 5.3 Individual valvular assessment
- 5.4 Recent techniques
- References
- Chapter 6. Software-based analysis for computed tomography coronary angiography: current status and future aspects
- Abstract
- 6.1 Introduction
- 6.2 Coronary artery calcification measurement
- 6.3 Software-based plaque analysis
- 6.4 Quantitative analysis for obstructive coronary artery
- 6.5 Computational fluid dynamics
- 6.6 Anatomical 2D bull’s eye display
- 6.7 Territorial analysis with Voronoi diagram
- 6.8 Nobel analysis for computed tomography angiography
- 6.9 Computed tomography myocardial perfusion imaging
- 6.10 The analysis of dynamic images by motion coherence technique
- 6.11 Closing remarks
- References
- Further reading
- Chapter 7. Medical image analysis for the early prediction of hypertension
- Abstract
- 7.1 Introduction
- 7.2 Methodology
- 7.3 Experimental results
- 7.4 Discussion
- 7.5 Conclusion and future work
- References
- Chapter 8. Left ventricle segmentation and quantification using deep learning
- Abstract
- 8.1 Heart: anatomy, function, and diseases
- 8.2 Left ventricle segmentation and quantification
- 8.3 Related work on left ventricle segmentation and quantification
- 8.4 Methods
- 8.5 Cardiac segmentation
- 8.6 Experimental results
- 8.7 Discussion
- References
- Chapter 9. Cardiac magnetic resonance imaging of cardiomyopathy
- Abstract
- 9.1 Introduction
- 9.2 Iron overload cardiomyopathy
- 9.3 Idiopathic dilated cardiomyopathy
- 9.4 Hypertrophic cardiomyopathy
- 9.5 Sarcoidosis
- 9.6 Myocarditis
- 9.7 Amyloidosis
- 9.8 Left ventricle noncompaction
- 9.9 Arrhythmogenic right ventricular dysplasia/cardiomyopathy
- 9.10 Stress-induced (Takotsubo) cardiomyopathy
- 9.11 Fabry disease
- 9.12 Muscular dystrophy
- References
- Chapter 10. Magnetic resonance imaging of pericardial diseases
- Abstract
- 10.1 Introduction
- 10.2 Normal pericardium
- 10.3 Pericarditis
- 10.4 Pericardial effusion
- 10.5 Pericardial hematoma
- 10.6 Cardiac tamponade
- 10.7 Pericardial constriction
- 10.8 Pericardial neoplasms
- 10.9 Pericardial cyst and diverticulum
- 10.10 Congenital absence of pericardium
- 10.11 Pericardial diaphragmatic hernia
- 10.12 Extracardiac lesions
- References
- Chapter 11. Imaging modalities for congenital heart disease and genetic polymorphism associated with coronary artery and cardiovascular diseases
- Abstract
- 11.1 Introduction
- 11.2 Sources of information and search
- 11.3 Study selection
- 11.4 Diet and cardiovascular disease risk
- 11.5 High-density lipoprotein cholesterol
- 11.6 Low-density lipoprotein cholesterol
- 11.7 Triglycerides
- 11.8 Inherited genetic susceptibility
- 11.9 Imaging strategy and techniques
- 11.10 Plain radiography
- 11.11 Echocardiography
- 11.12 Computed tomography
- 11.13 Methodology
- 11.14 Results and discussion
- 11.15 Results and discussion of SMARCA4 gene polymorphism
- 11.16 Conclusion
- Author contributions
- References
- Index
- Edition: 1
- Published: November 22, 2022
- No. of pages (Paperback): 234
- No. of pages (eBook): 234
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780128219836
- eBook ISBN: 9780128227053
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