Latest AI and machine learning research in radiology for healthcare professionals.
Large vision-language models (VLMs) demonstrate strong performance in medical image understanding, b...
Background: Radiogenomics allows identification of radiological biomarkers for genomic phenotypes. I...
Quantitative cardiac magnetic resonance imaging (MRI) enables non-invasive myocardial tissue charact...
Recently, diffusion models have attracted considerable attention for magnetic resonance image recons...
Deep learning models in medical imaging often fail when deployed in new clinical environments due to...
High-resolution postmortem (ex vivo) magnetic resonance imaging enables detailed examination of brai...
Aim: Exercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercis...
Imaging genetics aims to understand how genetic variation influences brain structure and cognitive f...
Deep learning-based organs/structures-at-risk(OARs) auto-contouring models can improve radiotherapy ...
Vision foundation models are increasingly moving beyond 2D to volumetric domains such as 3D medical ...
We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked aut...
Interpreting quantitative CT biomarkers, such as organ volume and tissue attenuation, requires large...
Graph-based learning on functional magnetic resonance imaging (fMRI) has shown strong potential for ...
The opaque nature of deep learning models remains a significant barrier to their clinical adoption i...
Self-supervised pretraining has become the mainstream approach for learning MRI representations from...
Tau protein aggregation in the brain is a hallmark of Alzheimer's disease (AD). Positron emission to...
Purpose: To demonstrate the feasibility of prostate MRI at low-field and provide an optimised low-fi...
Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide,...
Severe fetal growth restriction (sFGR) affects 5 to 10% of pregnancies worldwide and is a major cont...
Medical image super-resolution (MedSR) is essential for improving diagnostic precision across divers...
Magnetic Resonance Imaging (MRI) acquisition remains a time-intensive and patient-straining process,...