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Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting [Kõva köide]

Edited by (Research Associate, University College London, UK), Edited by , Edited by (Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands), Edited by (Associate professor, University of Barcelona, Spain), Edited by
  • Formaat: Hardback, 478 pages, kõrgus x laius: 235x191 mm, kaal: 1110 g
  • Sari: The MICCAI Society book Series
  • Ilmumisaeg: 05-Dec-2016
  • Kirjastus: Academic Press Inc
  • ISBN-10: 012811018X
  • ISBN-13: 9780128110188
Teised raamatud teemal:
Computing and Visualization for Intravascular Imaging and Computer-Assisted StentingSuurem pilt
  • Formaat: Hardback, 478 pages, kõrgus x laius: 235x191 mm, kaal: 1110 g
  • Sari: The MICCAI Society book Series
  • Ilmumisaeg: 05-Dec-2016
  • Kirjastus: Academic Press Inc
  • ISBN-10: 012811018X
  • ISBN-13: 9780128110188
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128110188.html
Märksõnad:

This book presents imaging, treatment and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases.

After setting out the technical and clinical challenges of vascular imaging and stenting, this book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges.

The reader will learn:

  • The main challenges in endovascular procedures
  • New applications of intravascular imaging
  • The latest advances in computer assisted stenting
  • Brings together scientific researchers, medical experts and industry partners working in the field of endovascular imaging and stenting procedures within different anatomical regions
  • An introduction to the clinical workflow and current challenges in endovascular Interventions
  • A review of the state-of-the-art methodologies in endovascular imaging and their applications
  • Presents outstanding questions still to be solved and discusses future research

Muu info

Teaches users how to develop clinically relevant solutions for computer-assisted endovascular procedures
Contributors xi
About the Editors xv
Preface xix
Section I Clinical Introduction
1(106)
1 Intravascular Imaging to Assess Coronary Atherosclerosis and Percutaneous Coronary Interventions
3(30)
S. Carlier
K. Houissa
1 Intravascular Imaging Development
3(4)
2 Safety of Intravascular Imaging
7(1)
3 Intravascular Imaging Versus Coronary Angiography
8(1)
4 Intravascular Imaging Assessment of Plaque Progression/Regression
9(4)
5 Intravascular Imaging Assessment of Lesions to Be Revascularized, or Not
13(3)
6 Intravascular Imaging Assessment of Percutaneous Interventions
16(7)
7 Future Developments and Final Word
23(10)
References
24(9)
2 Atherosclerotic Plaque Progression and OCT/IVUS Assessment
33(20)
J. Rigla
1 Aims and Introduction
33(1)
2 Description of Atherosclerosis Lesions in Children, Adults, and Elderly Population
34(2)
3 Atherosclerosis Histologist Classification
36(2)
4 Phases of Progression of Atherosclerosis Disease
38(2)
5 OCT
40(2)
6 IVUS
42(4)
7 Vulnerable Plaques
46(1)
8 Summary
46(7)
References
48(5)
3 AAA Treatment Strategy Change Over Time
53(26)
R. Ghotbi
R. Mansour
1 Introduction
54(2)
2 Pathogenesis
56(4)
3 Open Surgical Repair
60(2)
4 Endovascular Aneurysm Repair
62(3)
5 Preoperative Planning
65(9)
6 Imaging for Planning the Intraoperative Procedure and Postoperative Follow-Up
74(5)
References
76(3)
4 Overview of Different Medical Imaging Techniques for the Identification of Coronary Atherosclerotic Plaques
79(28)
A. Taki
A. Kermani
S.M. Ranjbamavazi
A. Pourmodheji
1 Introduction
79(1)
2 Clinical Overview
80(5)
3 Imaging Techniques
85(18)
4 Discussion
103(4)
References
105(2)
Section II Vascular and Intravascular Analysis of Plaque
107(118)
5 Implications of the Kinematic Activity of the Atherosclerotic Plaque: Analysis Using a Comprehensive Framework for B-Mode Ultrasound of the Carotid Artery
109(22)
A. Gastounioti
S. Golemati
P. Mermigkas
M. Prevenios
K.S. Nikita
1 Introduction
109(2)
2 Study Population and Ultrasound Image Data
111(1)
3 A Comprehensive Framework for Quantifying the Arterial Wall Motion
112(2)
4 Bilateral Asymmetry in Kinematic Features of Atherosclerotic Arteries
114(5)
5 Risk Stratification Driven by the Kinematic Activity of the Arterial Wall
119(6)
6 Data Mining of Association-Based Phenotypic Networks
125(2)
7 Conclusion
127(4)
Acknowledgments
128(1)
References
128(3)
6 Right Generalized Cylinder Model for Vascular Segmentation
131(26)
L. Florez-Valencia
M. Orkisz
1 Motivation
132(1)
2 Direct Model
133(8)
3 Parameters Inversion
141(8)
4 Model-Guided Image Segmentation
149(5)
5 Conclusions
154(3)
References
155(2)
7 Domain Adapted Model for In Vivo Intravascular Ultrasound Tissue Characterization
157(26)
S. Conjeti
A.G. Roy
D. Sheet
S. Carlier
T. Syeda-Mahmood
N. Navab
A. Katouzian
1 Introduction
158(3)
2 State of the Art
161(2)
3 Mathematical Modeling of Ultrasonic Backscattering and Signal Propagation Physics in Heterogeneous Tissues
163(7)
4 Domain Adaptation for In Vivo TC
170(3)
5 Experiments and Discussion
173(5)
6 Conclusions
178(5)
Acknowledgments
179(1)
References
179(4)
8 Intracoronary Optical Coherence Tomography
183(42)
G.J. Ughi
T. Adriaenssens
1 Introduction
183(6)
2 Coronary Imaging
189(12)
3 OCT Clinical Research
201(1)
4 OCT Image Processing
202(5)
5 Future Outlook
207(18)
References
216(9)
Section III Vascular Biomechanics and Modeling
225(88)
9 Vascular Hemodynamics with Computational Modeling and Experimental Studies
227(26)
S. Beier
J. Ormiston
M. Webster
J. Cater
S. Norris
P. Medrano-Gracia
A. Young
B. Cowan
1 Vascular Hemodynamics and Atherosclerosis
228(2)
2 Vessel Geometry
230(2)
3 Computational (CFD) Modeling
232(3)
4 Experimental Studies
235(6)
5 Data Postprocessing, Co-Registration, and Comparison
241(2)
6 Accuracy and Reliability
243(3)
7 Current Developments
246(7)
Acknowledgments
247(1)
References
247(6)
10 Arterial Flow Impact on Aneurysmal Hemodynamics
253(36)
H.G. Morales
O. Bonnefous
1 Introduction
254(2)
2 Modeling Aneurysm Hemodynamics
256(1)
3 Contributions of this
Chapter
257(7)
4 Part 1: Peak-Systolic and Maximum Hemodynamic Condition
264(9)
5 Part 2: Characteristic Curves of Intra-Aneurysmal Hemodynamics
273(11)
6 Conclusions
284(5)
Acknowledgments
284(1)
References
285(4)
11 Toward a Mechanical Mapping of the Arterial Tree: Challenges and Potential Solutions
289(24)
R.L. Maurice
K.Y.H. Chen
D. Burgner
L.B. Daniels
L. Vaujois
N. Idris
J.-L. Bigras
N. Dahdah
1 Overview and Objectives
289(1)
2 Arterial Pathophysiology, Mechanics, and Stiffness Assessment
290(4)
3 Method: Imaging-Based Biomarker (ImBioMark)
294(5)
4 ImBioMark: Applications on Carotid, Brachial, and Aorta Arteries
299(8)
5 Discussion
307(1)
6 Conclusion
308(5)
Acknowledgments
309(1)
References
309(4)
Section IV Computer-Assisted Stenting
313(132)
12 Computerized Navigation Support for Endovascular Procedures
315(26)
P. Fallavollita
S. Demirci
1 Introduction
315(2)
2 Simulation for Training
317(5)
3 Interventional Navigation Support
322(19)
References
337(4)
13 Interventional Quantification of Cerebral Blood Flow
341(30)
S. Demirci
M. Kowarschik
1 Introduction to the Clinical Value of Blood Flow Quantification
341(3)
2 Blood Flow Assessment Using Angiographic X-Ray Imaging
344(27)
References
367(4)
14 Virtual Stenting for Intracranial Aneurysms: A Risk-Free, Patient-Specific Treatment Planning Support for Neuroradiologists and Neurosurgeons
371(42)
P. Berg
L. Daroczy
G. Janiga
1 Intracranial Aneurysms
372(1)
2 Existing Approaches---From Precise to Pragmatic
373(14)
3 Validation---The Curse of Computational Predictions
387(2)
4 Selected Applications---How Numerical Models Can Assist
389(17)
5 Future Directions---Chances and Limitations
406(7)
Acknowledgments
407(1)
References
407(6)
15 Preoperative Planning of Endovascular Procedures in Aortic Aneurysms
413(32)
I. Macia
J.H. Legarreta
K. Lopez-Linares
C. Doblado
L. Kabongo
1 Introduction
413(2)
2 Overview of Endograft Sizing for Aortic Aneurysms
415(1)
3 Vascular Segmentation
416(3)
4 Vascular Analysis
419(5)
5 Quantitative Image Analysis
424(5)
6 Visualization and Workflow
429(8)
7 Endograft Sizing Software
437(3)
8 Conclusions and Future Perspectives 439 References
440(5)
Index 445
Dr. Simone Balocco is Associate Professor of the University of Barcelona, Departement of Mathematics and Informatics, and is senior researcher at the Computer Vision Center, Bellaterra. He obtained a PhD degree in Acoustics at the laboratory Creatis, Lyon and in Electronic and Telecommunication in MSD Lab, University of Florence (Italy). He performed a post-doc at the laboratory CISTIB, at the University Pompeu Fabra. Dr. Balocco main research interest are pattern recognition and computer vision methods for the computer-aided detection of clinical pathologies. In particular his research focuses on Ultrasound and Magnetic Imaging applications and vascular modelling. In 2011, Maria A. Zuluaga obtained her PhD degree from Université Claude Bernard Lyon I investigating automatic methods for the diagnosis of coronary artery disease. After a year as a postdoctoral fellow at the European Synchrotron Radiation Facility (Grenoble, France), she joined University College London, in March 2012, as a Research Associate to work on cardiovascular image analysis and computer-aided diagnosis of cardiovascular pathologies. Since August 2014, she is part of the Image-guided fetal surgery project (GIFT-Surg) project as a senior research associate. Guillaume Zahnd received his engineering degree from the National Institutes of Applied Science (INSA-Lyon, France) in 2007, and obtained his PhD from CREATIS laboratory, University of Lyon (France) in 2012. In 2013, he joined the Biomedical Imaging Group Rotterdam, Erasmus MC (Netherlands) as a PostDoc researcher. From 2016, he is a research fellow in the Imaging-based Computational Biomedicine laboratory at Nara Institute of Science and Technology (Japan). His work focuses on image processing methodologies towards cardiovascular risk assessment. His field of interest includes vascular imaging, image-based biomarkers, ultrasound, intracoronary optical coherence tomography, motion tracking, contour segmentation and machine learning. Su-Lin Lee received the MEng. degree in information systems engineering and Ph.D. degree from Imperial College London, London, U.K., in 2002 and 2006, respectively, for her work on statistical shape modelling and biomechanical modelling. She is currently a Lecturer at The Hamlyn Centre for Robotic Surgery and the Department of Computing, Imperial College London. Her current research focuses on machine learning and shape modelling with application to guidance in cardiovascular interventions. Of particular interest to her are improved navigation and decision support for safer and more efficient robotic-assisted minimally invasive cardiovascular procedures. Stefanie Demirci is a Postdoctoral Researcher and Research Manager at Technical University of Munich (TUM), Germany. She received her Ph.D. degree from the same institution in 2011 for her work on novel approaches to computer assisted endovascular procedures. After being a Postodctoral Fellow at the SINTEF Medical Technology lab in Trondheim, Norway, she returned back to TUM where she is currently teaching Interventional Imaging and Image Processing and managing the Computer Aided medical Procedures (CAMP) lab. Her current research focuses on multi-modal imaging and image processing, machine learning and biomedical gamification with particular interest in crowd sourcing for biomedical ground truth creation.