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Emerging Techniques in Imaging, Modelling and Visualization for Cardiovascular Diagnosis and Therapy
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The goal of this Special Issue is to disseminate emerging techniques and innovative solutions that comprehensively address unmet needs in cardiovascular disease and can be rapidly translated into the clinical arena in order to significantly improve diagnostic accuracy and precision in treatment delivery, as well as to enhance therapy guidance and procedural success. The volume includes research contributions from cross-disciplinary scientists and professionals who work in the cardiovascular field at the interface of basic and translational research, clinical practice, medical (bio)physics, engineering, mathematics, and computer science. Several compelling contributions are focused on the development of advanced techniques in cardiovascular imaging (MRI, CT, ultrasound, optics) to investigate structure–function interaction and identify pathology, image analysis (e.g. registration, segmentation, visualization), deep-learning/AI classification methods to better characterize tissue and physiological signals, novel preclinical experimental models and clinical approaches employed in electro-anatomical mapping and image-aided therapies (e.g., cardiac ablation, resynchronization), as well as innovative interventional procedures for vascular applications.
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Keywords
- 3D registration
- 3D TEE
- 3D-printing
- arrhythmia
- Atrial Fibrillation
- augmentation
- Biomechanics
- biophysical modelling
- cardiac function
- cardiac image segmentation
- cardiac imaging
- cardiac magnetic resonance imaging
- cardiac microstructure
- Cardiac MRI
- cardiac radiofrequency ablation
- cardiac resynchronization therapy
- cardiac segmentation
- cardiometabolic risk
- cardiotoxicity
- cardiovascular imaging
- carotid intima-media thickness
- cerebral blood flow
- chemotherapy
- Childhood obesity
- chronic infarction
- Circle of Willis variants
- compounded echocardiography
- Computational Cardiology
- coronary vasculature
- CRT-EPiggy19 challenge
- Data assimilation
- deep learning
- Diffusion Tensor Imaging
- disentangled representation
- domain invariant features
- doxorubicin
- Electrophysiology
- Fibrosis
- fractional flow reserve
- generative adversarial network
- hemodynamics
- History of engineering & technology
- image quality
- image-based kinematics
- in vivo cDTI
- inverse models
- inverse problems
- Layfomm-40
- left ventricle segmentation
- lumped parameter model
- Machine learning
- meshless model
- mitral valve
- monogenic signal
- mosaicing
- MRI
- multimodal
- mutual information
- n/a
- parameter optimisation
- patient-specific models
- physical simulation
- radial diffusivity
- Reconstruction
- reduced order model
- reliability and robustness
- sensitivity analysis
- simulation training
- smoothed particle hydrodynamics
- subclinical atherosclerosis
- swine infarction model
- Technology, engineering, agriculture
- Technology: general issues
- thermochromic pigments
- tissue mechanics
- variational autoencoder
- voltage mapping
- volume stitching
Links
DOI: 10.3390/books978-3-0365-7101-0Editions