Motion artifacts occur in magnetic resonance imaging (MRI) due to the motion or movement
of the object being scanned. Motion artifacts can have various origins such as voluntary or …

Cardiac MRI segmentation is a significant research area in medical image processing,
holding immense clinical and scientific importance in assisting the diagnosis and treatment …

In medical images, the edges of organs are often blurred and unclear. Existing semi-
supervised image segmentation methods rarely model edges explicitly. Thus most methods …

Introduction Automatic segmentation of the left atrium (LA) constitutes a crucial pre-
processing step in evaluating heart structure and function during clinical interventions, such …

In this paper, we propose a variational approach towards denoising magnetic resonance
images (MRI) corrupted by spatially variant and signal-dependent Rician noise in a deep …

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

Cardiac segmentation plays a crucial role in computer-aided diagnosis of cardiac diseases.
Nevertheless, the task of cardiac segmentation is inherently arduous due to the complex …

Magnetic resonance imaging (MRI) is a non-invasive technique used in cardiac diagnosis.
Using it, specialists can measure the masses and volumes of the right ventricle (RV), left …

Cardiac segmentation is a critical task in medical imaging, essential for detailed analysis of
heart structures, which is crucial for diagnosing and treating various cardiovascular …

Accurate segmentation of myocardial scar tissue on late gadolinium enhancement-magnetic
cardiac resonance imaging (LGE-CMR) is exceptionally vital for clinical applications …