Recent advancements in Artificial Intelligence (AI) have significantly influenced the field of
Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our paper …

Left atrial (LA) fibrosis plays a vital role as a mediator in the progression of atrial fibrillation.
3D late gadolinium-enhancement (LGE) MRI has been proven effective in identifying LA …

Artificial intelligence (AI) integration in cardiac magnetic resonance imaging presents new
and exciting avenues for advancing patient care, automating post-processing tasks, and …

Abstract Cardiac Magnetic Resonance (CMR) Imaging is currently considered the gold
standard imaging modality in cardiology. However, it is accompanied by a tradeoff between …

Despite the extensive utilization of deep learning in medical image segmentation, the
achieved accuracy remains inadequate for clinical requirements due to the scarcity of …

Tensor-based representations are being increasingly used to represent complex data types
such as imaging data, due to their appealing properties such as dimension reduction and …

Accurate segmentation of the left ventricle (LV) using echocardiogram (Echo) images is
essential for cardiovascular analysis. Conventional techniques are labor-intensive and …

Dynamic 3D imaging is increasingly used to study evolving objects. We address the problem
of detecting and tracking simple objects that merge or split in time. Common solutions …

Accurate and precise segmentation of the left atrium (LA) is crucial in the early diagnosis
and treatment of atrial fibrillation (AF), which is the most common heart rhythm disease in …

Accurate segmentation of the ventricles plays a crucial role in determining cardiac functional
parameters such as ventricular volume, ventricular mass, or ejection fraction. However, poor …