| 청구기호 |
RC670 .R348 2019eb vol. 1 |
| 다른형태 서명 |
Stent applications.
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| 형태사항 |
1 online resource (various pagings) : illustrations (some color).
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| 총서명 |
[IOP release 6]
IOP expanding physics, 2053-2563
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| 언어 |
English |
| 일반주기 |
"Version: 20190801"--Title page verso.
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| 서지주기 |
Includes bibliographical references.
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| 내용 |
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 perspectives
2. 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. Conclusions
section 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 conclusions
4. 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. Conclusion
5. 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 work
section 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. Conclusion
7. 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 work
8. 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. Conclusion
9. 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. Conclusions
10. 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 application
11. 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. Conclusion
section 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. Conclusion
13. 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. Conclusions
14. 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.
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| 주제 |
Cardiovascular system --Diseases --Imaging.
Cardiovascular system --Diseases --Computer simulation.
Stents (Surgery)
Cardiovascular Diseases --diagnostic imaging.
Cardiovascular Diseases.
Computer Simulation.
Stents.
Biomedical engineering. --bicssc
TECHNOLOGY & ENGINEERING / Biomedical. --bisacsh
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| 보유판 및 특별호 저록 |
Print version: 9780750319959
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| ISBN |
9780750319973, 9780750319966, 9780750319959 |
| 기타 표준번호 |
10.1088/2053-2563/ab01fa |
| QR CODE |
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