Article
Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using...
Chapter and Conference Paper
Convolutional neural networks (CNN), while effective in medical diagnostics, have shown concerning biases against underrepresented patient groups. In this study, we provide an in-depth exploration of these bia...
Article
Radiomics is an emerging technique for the quantification of imaging data that has recently shown great promise for deeper phenoty** of cardiovascular disease. Thus far, the technique has been mostly applied...
Chapter and Conference Paper
In recent years, deep learning models have considerably advanced the performance of segmentation tasks on Brain Magnetic Resonance Imaging (MRI). However, these models show a considerable performance drop when...
Book and Conference Proceedings
12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Revised Selected Papers
Chapter and Conference Paper
Accurate segmentation of the cardiac boundaries in late gadolinium enhancement magnetic resonance images (LGE-MRI) is a fundamental step for accurate quantification of scar tissue. However, while there are ma...
Chapter and Conference Paper
Accurate segmentation of pathological tissue, such as scar tissue and edema, from cardiac magnetic resonance images (CMR) is fundamental to the assessment of the severity of myocardial infarction and myocardia...
