Multi-modality cardiac imaging plays a key role in the management of patients with
cardiovascular diseases. It allows a combination of complementary anatomical …

Data for healthcare is diverse and includes many different modalities. Traditional
approaches to Artificial Intelligence for cardiovascular disease were typically limited to …

Cardiovascular imaging has significantly evolved since the turn of the century. Progress in
the last two decades has been marked by advances in every modality used to image the …

Introduction: Non-invasive imaging plays a critical role in managing patients with
cardiovascular disease. Although subjective visual interpretation remains the clinical …

The procedural success of cardiovascular and structural interventions depends on adequate
pre-and intraprocedural imaging. Multimodal imaging utilizing several techniques provides …

Noninvasive cardiac imaging is widely used for the diagnosis and management of cardiac
patients. The increasing demand for cardiac imaging begins to exceed the number of …

Background Machine learning (ML) represents a family of algorithms that has rapidly
developed within the last years in a wide variety of knowledge areas. ML is able to elucidate …

Three-dimensional (3-D) imaging of the heart is a rapidly developing area of research in
medical imaging. Advances in hardware and methods for fast spatio-temporal cardiac …

The use of medical imaging has substantially increased over the past decade, thanks to the
technological advancements evident from the dramatic improvement in the sensitivity and …

Personalised medicine is based on the principle that each body is unique and will respond
to therapies differently. In cardiology, characterising patient specific cardiovascular …