Emerging Techniques in Imaging, Modelling and Visualization for Cardiovascular Diagnosis and Therapy

• Other Authors: Pop, Mihaela (Editor), Linte, Cristian A. (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: Technology: general issues; History of engineering & technology; cardiometabolic risk; carotid intima-media thickness; childhood obesity; subclinical atherosclerosis; reduced order model; atrial fibrillation; Circle of Willis variants; cerebral blood flow; sensitivity analysis; cardiac MRI; machine learning; left ventricle segmentation; cardiac function; diffusion tensor imaging; in vivo cDTI; chronic infarction; cardiac microstructure; radial diffusivity; swine infarction model; cardiac image segmentation; reliability and robustness; deep learning; cardiac magnetic resonance imaging; inverse models; data assimilation; cardiovascular imaging; image-based kinematics; biomechanics; tissue mechanics; hemodynamics; patient-specific models; coronary vasculature; lumped parameter model; fractional flow reserve; computational cardiology; compounded echocardiography; volume stitching; 3D registration; mosaicing; 3D TEE; mitral valve; monogenic signal; cardiac imaging; multimodal; electrophysiology; biophysical modelling; inverse problems; parameter optimisation; smoothed particle hydrodynamics; meshless model; cardiac resynchronization therapy; CRT-EPiggy19 challenge; cardiac radiofrequency ablation; 3D-printing; Layfomm-40; physical simulation; simulation training; thermochromic pigments; cardiotoxicity; MRI; fibrosis; chemotherapy; doxorubicin; voltage mapping; arrhythmia; augmentation; cardiac segmentation; domain invariant features; disentangled representation; generative adversarial network; image quality; mutual information; reconstruction; variational autoencoder; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.