Throughout the body, muscle structure and function can be interrogated using a variety of
noninvasive magnetic resonance imaging (MRI) methods. Recently, intravoxel incoherent …

Purpose Earlier work showed that IVIM‐NETorig, an unsupervised physics‐informed deep
neural network, was faster and more accurate than other state‐of‐the‐art intravoxel …

Purpose This prospective clinical study assesses the feasibility of training a deep neural
network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion‐weighted …

Non-invasive estimation of brain microstructure features using diffusion MRI (dMRI)—known
as Microstructure Imaging—has become an increasingly diverse and complicated field over …

Magnetic resonance imaging (MRI) has the potential to improve our understanding of
diabetes and improve both diagnosis and monitoring of the disease. Although the spatial …

Objectives Standardization is an important milestone in the validation of DWI-based
parameters as imaging biomarkers for renal disease. Here, we propose technical …

Background Radiomics is aimed at image-based tumor phenotyping, enabling application
within clinical-decision-support-systems to improve diagnostic accuracy and allow for …

Purpose The intravoxel incoherent motion (IVIM) model for DWI might provide useful
biomarkers for disease management in head and neck cancer. This study compared the …

The intravoxel incoherent motion (IVIM) model allows to map diffusion (D) and perfusion-
related parameters (F and D*). Parameter estimation is, however, error-prone due to the non …

Patient stratification based on biological variation in pancreatic ductal adenocarcinoma
(PDAC) subtypes could help to improve clinical outcome. However, noninvasive assessment …