We propose the Generalized Probabilistic U-Net, which extends the
Probab...
Purpose: Coronary artery calcium (CAC) score, i.e. the amount of CAC
qua...
With an increase in deep learning-based methods, the call for explainabi...
Deep learning-based whole-heart segmentation in coronary CT angiography
...
In this study, we propose a fast and accurate method to automatically
lo...
Treatment of patients with obstructive coronary artery disease is guided...
Primary tumors have a high likelihood of developing metastases in the li...
Spherical deconvolution is a widely used approach to quantify fiber
orie...
Diffusion weighted magnetic resonance imaging is a noninvasive imaging
t...
Purpose: This study demonstrates a proof of concept of a method for
simu...
Purpose: To understand and characterize noise distributions in parallel
...
In patients with obstructive coronary artery disease, the functional
sig...
Quantification of cerebral white matter hyperintensities (WMH) of presum...
Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruc...
Coronary artery centerline extraction in cardiac CT angiography (CCTA) i...
Cardiovascular disease (CVD) is a leading cause of death in the lung can...
Image registration, the process of aligning two or more images, is the c...
Knowledge of the noise distribution in magnitude diffusion MRI images is...
Different types of atherosclerotic plaque and varying grades of stenosis...
Coronary artery calcium (CAC) burden quantified in low-dose chest CT is ...
In patients with coronary artery stenoses of intermediate severity, the
...
Heavy smokers undergoing screening with low-dose chest CT are affected b...
Segmentation of the heart in cardiac cine MR is clinically used to quant...
Automatic segmentation of medical images is an important task for many
c...
Automatic segmentation in MR brain images is important for quantitative
...
The proliferative activity of breast tumors, which is routinely estimate...