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Cardiovascular imaging and image analysis

Author: Ayman S El-Baz; Jasjit S Suri
Publisher: Boca Raton, FL : CRC Press, [2019]
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This will be a comprehensive multi-contributed reference work that will detail the latest developments in spatial, temporal, and functional cardiac imaging. It will include several prominent imaging modalities such as MRI, CT, and PET technologies. There will be special emphasis placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. Novel 4D  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Cardiovascular imaging and image analysis.
Boca Raton : Taylor & Francis, [2019]
(DLC) 2018022105
Material Type: Document
Document Type: Book, Computer File
All Authors / Contributors: Ayman S El-Baz; Jasjit S Suri
ISBN: 9780429441493 0429441495 9780429806223 0429806221 9780429806216 0429806213 9780429806209 0429806205 9781498798440 1498798446
OCLC Number: 1035774806
Description: 1 online resource (xxxii, 436 pages)
Contents: Cover; Half Title; Title Page; Copyright Page; Dedication; Contents; Preface; Acknowledgments; About the Editors; Contributors; Chapter 1: Detection of Cerebrovascular Changes Using Magnetic Resonance Angiography; Contents; 1.1. Introduction; 1.2. Methods; 1.2.1. Patient Demographics; 1.2.2. Data Analysis; 1.2.2.1. Manual Segmentation of Training Slices; 1.2.2.2. Automatic Segmentation; 1.2.2.3. Voxel Matching; 1.2.2.4. Generation of Probability Distribution Function and Validation; 1.2.2.5. Calculation of Cumulative Distribution Function; 1.2.3. Statistical Analysis 1.2.4. 3D Reconstruction of the Cerebral Vasculature1.3. Results; 1.4. Discussion; 1.5. Limitations; 1.6. Conclusion; Appendices; A. Initialization Sequentially Using EM Algorithm; B. Refining LCDGs using Modified EM Algorithm; References; Chapter 2: Segmentation of Blood Vessels Using Magnetic Resonance Angiography Images; Contents; 2.1. Introduction; 2.2. Probability Model of Vascular Signals; 2.3. Adaptive Model of Multi-Modal MRA; 2.4. Segmentation of Blood Vessels; 2.5. Validation; 2.6. Conclusion; References; Chapter 3: Vascular Tree Segmentation from Different Image Modalities 3.1. Introduction; 3.2. Surface Modelling by Level Sets; 3.3. Statistical Gray Level Distribution Model; 3.3.1. Modified EM Algorithm for LCGs; 3.3.2. Sequential EM-Based Initialization; 3.3.3. Classification of the Model Components; 3.4. Evolutionary Surface Model; 3.4.1. PDE System; 3.4.2. Data Consistency Coefficient hi(I); 3.5. Evaluation of the Segmentation Approach; 3.6. Experimental Results; 3.6.1. Separation of Blood Vessels in MRA-TOF Images; 3.6.2. Extraction of Blood Vessels from Phase Contrast Images; 3.6.3. Extraction of the Aorta from CTA Images 3.7. Conclusion and Future ResearchReferences; Chapter 4: Accurate Unsupervised 3D Segmentation of Blood Vessels Using Magnetic Resonance Angiography; Contents; 4.1. Introduction; 4.2. Slice-Wise Segmentation with the LCDG Models; 4.3. Experimental Results; 4.3.1. Segmentation of Natural TOF --
and PC-MRA Images; 4.3.2. Validating the Segmentation Accuracywith Special Phantoms; 4.4. Conclusion; Appendices; A. Sequential EM-based initialization; B. Modified EM algorithm for refining LCDGs; References; Chapter 5: An Unsupervised Parametric Mixture Model for Automatic Cerebrovascular Segmentation 5.1. Introduction; 5.2. Magnetic Resonance Imaging; 5.3. Cerebrovascular Segmentation Using Magnetic Resonance Imaging; 5.3.1. Related Work on Cerebrovascular Segmentation; 5.3.2. Proposed Work; 5.3.3. Experimental Results; 5.4. Conclusion; References; Chapter 6: Left Atrial Scarring Segmentation from Delayed-Enhancement Cardiac MRI Images: A Deep Learning Approach; Contents; 6.1. Introduction; 6.1.1. Background; 6.1.2. Related Work; 6.1.3. Our Contributions; 6.2. Method; 6.2.1. Study Population; 6.2.2. MRI Protocol; 6.2.3. Multi-Atlas Whole Heart Segmentation (MA-WHS)
Responsibility: edited by Ayman El-Baz and Jasjit S. Suri.

Abstract:

This will be a comprehensive multi-contributed reference work that will detail the latest developments in spatial, temporal, and functional cardiac imaging. It will include several prominent imaging modalities such as MRI, CT, and PET technologies. There will be special emphasis placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. Novel 4D based approach will be a unique characteristic of this product--

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