Vascular and intravascular imaging trends, analysis, and challenges.
"Version: 20190801"--Title page verso.Includes bibliographical references.section I. Vascular and intravascular clinical analysis. 1. OCT in the evaluation of late stent pathology : restenosis, neoatherosclerosis and late malapposition -- 1.1. Stent evolution and late stent pathology -- 1.2. OCT characterization of late stent pathology -- 1.3. OCT evaluation of bioresorbable vascular scaffolds -- 1.4. Future perspectives2. Bioresorbable eluting scaffolds in the era of optical coherence tomography : real-world clinical practice -- 2.1. Introduction -- 2.2. Historical background and the search for the ideal bioresorbable scaffold -- 2.3. Bioresorbable scaffolds : current clinical evidence -- 2.4. The clinical utility of optical coherence tomography in the optimization of bioresorbable scaffolds -- 2.5. Bioresorbable scaffolds in real-world clinical settings -- 2.6. Conclusionssection II. Computer modeling and computational fluid hemodynamics. 3. Computer modeling of blood flow and plaque progression in the stented coronary artery -- 3.1. Introduction -- 3.2. Methods -- 3.3. Results -- 3.4. Discussion and conclusions4. Current status of computational fluid dynamics for modeling of diseased vessels -- 4.1. Introduction -- 4.2. Constitutive equation of blood flow in a diseased vessel -- 4.3. Viscoelastic models of diseased blood -- 4.4. CFD modeling of blood flow in a diseased vessel -- 4.5. Evaluation of the shear index on the vascular wall -- 4.6. Conclusion5. Fast virtual endovascular stenting : technique, validation and applications in computational haemodynamics -- 5.1. Motivation -- 5.2. Virtual stenting -- 5.3. The fast virtual stenting method -- 5.4. Validation--how accurate is accurate enough? -- 5.5. Discussion and future worksection III. Vessel and stent segmentation. 6. Graph-based cross-sectional intravascular image segmentation -- 6.1. Introduction -- 6.2. Pre-processing -- 6.3. Feature extraction -- 6.4. Single- and double-interface segmentation -- 6.5. Results : IVUS -- 6.6. Results : OCT -- 6.7. Conclusion7. Blind inpainting and outlier detection using logarithmic transformation and total variation -- 7.1. Introduction -- 7.2. Blind inpainting -- 7.3. Experimental results -- 7.4. Conclusions and future work8. Differential imaging for the detection of extra-luminal blood perfusion due to the vasa vasorum -- 8.1. Introduction -- 8.2. Methods -- 8.3. Results -- 8.4. Discussion -- 8.5. Conclusion9. Assessment of atherosclerosis in large arteries from PET images -- 9.1. Introduction -- 9.2. The formation of atherosclerosis -- 9.3. Management of atherosclerosis -- 9.4. Detection of atherosclerosis -- 9.5. Imaging of atherosclerosis with PET/CT -- 9.6. Discussion -- 9.7. Conclusions10. 3D-2D registration of vascular structures -- 10.1. Clinical interventions and 3D-2D registration -- 10.2. Mathematical definition of 3D-2D registration -- 10.3. Classification of 3D-2D registration -- 10.4. Review of registration bases -- 10.5. Review of transformation estimation approaches -- 10.6. Validation procedures -- 10.7. Validation of 3D-2D registration on cerebral angiograms -- 10.8. Challenges in translation to clinical application11. Endovascular navigation with intravascular imaging -- 11.1. Introduction -- 11.2. Existing research into intravascular imaging for navigation -- 11.3. IVUS for navigation -- 11.4. The future of intravascular imaging for navigation -- 11.5. Conclusionsection IV. Risk stratification in carotid and coronary artery. 12. A cloud-based smart IMT measurement tool for multi-center clinical trial and stroke risk stratification in carotid ultrasound -- 12.1. Introduction -- 12.2. Patient demographics and data acquisition -- 12.3. Methodology and cloud-based workflow -- 12.4. Results : measurements and visualization -- 12.5. Performance evaluation of the AtheroCloud(Tm) system -- 12.6. Discussion -- 12.7. Conclusion13. Stroke risk stratification and its validation using ultrasonic echolucent carotid wall plaque morphology : a machine learning paradigm -- 13.1. Introduction -- 13.2. Demographics, data acquisition and data preparation -- 13.3. Methodology -- 13.4. Experimental protocol -- 13.5. Results -- 13.6. Performance evaluation -- 13.7. Discussion -- 13.8. Conclusions14. An improved framework for IVUS-based coronary artery disease risk stratification by fusing wall-based and texture-based features during a machine learning paradigm -- 14.1. Introduction -- 14.2. Patient demographics and data acquisition -- 14.3. Methodology -- 14.4. Results -- 14.5. Performance evaluation -- 14.6. Discussion -- 14.7. Conclusion.Cardiovascular Diseases (CVDs) are responsible for a third of all deaths in women and more than a half in men. Despite continuous improvements in treatment devices and imaging, there is still a rise in the morbidity rate from CVDs each year. Compiled by experts in the field, a thorough investigation is given to current topics and problems relating to CVDs and it will enable the scientific and medical community to search for the most effective strategies for atherosclerotic for dealing with these diseases. As one of the most prominent diseases in our society, CVD requires dedicated analysis and investigation in order to reduce the mortality rate worldwide. Scholars, biomedical engineers and medical practitioners will greatly benefit from the detailed information in this book as it will give a better understanding of the causes, diagnosis and treatment of CVD.Academia and researchers, graduate students in medical imaging.Also available in print.Mode of access: World Wide Web.System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.Professor Petia Radeva is a senior researcher and Full professor at the University of Barcelona. She is the head of Computer Vision and Machine Learning Consolidated Research Group (CVUB) at the University of Barcelona and the head of Medical Imaging Laboratory (MiLab) of Computer Vision Centre, Spain. Her research interests include the development of Deep learning, Computer Vision and Lifelogging, and their applications to healthcare. Petia Radeva is IAPR Fellow and received Icrea Academia and the CIARP 'Aurora Pons Porrata' awards. Dr. Jasjit S Suri is an innovator, scientist, industrialist and an internationally known world leader in Biomedical Engineering, Sciences and its Management. He has numerous publications and is currently the Chairman of AtheroPoint, California, USA, dedicated in Stroke and Cardiovascular Imaging. He is a recipient of Life Time Achievement Award by Marquis (2018) and Fellow of American Institute of Medical and Biological Engineering (2004).Title from PDF title page (viewed on September 5, 2019).
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1 online resource (various pagings) :illustrations (some color).
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English
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9780750319973
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616.1/075
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Petia Radeva and Jasjit S. Suri.
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