Generalization to out-of-distribution (OOD) data is a capability natural to humans yet
challenging for machines to reproduce. This is because most learning algorithms strongly …

Cardiovascular disease (CVD) is the principal cause of mortality and morbidity globally. With
the pressures for improved care and translation of the latest medical advances and …

Convolutional neural networks have been widely applied to medical image segmentation
and have achieved considerable performance. However, the performance may be …

Dental caries is an infectious disease that deteriorates the tooth structure, with tooth cavities
as the most common result. Classified as one of the most prevalent oral health issues …

Motivation Medical images can provide rich information about diseases and their biology.
However, investigating their association with genetic variation requires non-standard …

Since the rise of deep learning (DL) in the mid-2010s, cardiac magnetic resonance (CMR)
image segmentation has achieved state-of-the-art performance. Despite achieving inter …

Cardiac anatomy and function vary considerably across the human population with
important implications for clinical diagnosis and treatment planning. Consequently, many …

Background Theoretically, artificial intelligence can provide an accurate automatic solution
to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic …

Cardiovascular magnetic resonance imaging is the gold standard for cardiac function
assessment. Quantification of clinical results (CR) requires precise segmentation. Clinicians …

Improving model's generalizability against domain shifts is crucial, especially for safety-
critical applications such as autonomous driving. Real-world domain styles can vary …