Radiology reading rooms are intentionally dim to optimise image contrast and reduce glare, supporting accurate interpretation. However, prolonged time in such settings coincides with reduce
READ MORE
Patient Views on AI in Radiology Artificial intelligence is moving more visibly into radiology and other areas of healthcare, raising new questions about how patients view its role in care.1
READ MORE
Interventional neuroradiology procedures have expanded over the past decade alongside technological development and rising clinical demand. These procedures often involve higher radiation d
READ MORE
Quantitative magnetic resonance imaging enables the mapping of tissue relaxation times and proton density, offering objective parameters to support clinical assessment. Synthetic MRI allows
READ MORE
Artificial intelligence has automated parts of scientific work for years, but not the full research cycle. The AI Scientist is an AI system that generates research ideas, runs experiments,
READ MORE
Healthcare environments combine valuable data, fragmented security standards and extensive networks of connected systems, often operating on legacy software. These conditions create multipl
READ MORE
Breast lesion classification can combine mammography and contrast-enhanced imaging within a multimodal deep learning workflow, as reported in a recent study published in the Journal of Bio
READ MORE
CT lung cancer screening is expanding in the UK, but scanner settings and reconstruction methods still vary and can affect both radiation dose and the accuracy of lung nodule measurement. C
READ MORE
Ultrasound image segmentation is evolving quickly as deep learning methods spread across breast imaging, cardiology, obstetrics and other clinical applications. A systematic review publishe
READ MORE
Artificial intelligence can support spine alignment assessment in adolescent idiopathic scoliosis, but performance often falls when radiographs come from different hospitals with different
READ MORE
