A novel AI-based method can distinguish between progressive brain tumours and radiotherapy-induced necrosis on advanced MRI. This could help clinicians more accurately identify and treat the issues.
Philips and Cortechs.ai have extended their collaboration to integrate AI-enabled quantitative neuroimaging analytics directly into MR systems. The partnership aims to provide radiologists with automated, objective measurements of brain structures and lesions to support diagnosis and monitoring of neurological conditions.
A patient reports with chest pain, but in the coronary angiogram, the main heart arteries look clear, so it cannot be angina – right? A new study reveals that this approach can easily lead to misdiagnosis.
Metal-organic frameworks (MOFs) serve as the basis for a novel type of MRI contrast agent, which the developers hope can outperform current agents while being less toxic for the patient.
Researchers developed an AI-assisted brain atlas for visualization at microscopic detail using MRI scans. The tool could transform early detection of Alzheimer's and other neurological diseases.
About 60% women in Europe enrolled in a national breast cancer screening programme who have a screening mammogram can feel reasonably confident that radiologists will be able to diagnose early-stage breast cancer. But what about the 30% categorised as having dense breasts, and the 10% who have extremely dense breasts? At the 2025 SBI (Society of Breast Imaging) Breast Imaging Symposium held in…
At the 2025 ESMRMB Annual Meeting in Marseille, speakers made a strong case for what remains an outsider in radiology: low-field MRI. Despite its affordability, improved performance, and reduced environmental footprint, the technology continues to face scepticism – not from regulators or patients, but from radiologists themselves.
An international team has developed an AI model that brings together medical imaging data and clinical information to calculate the risk of breast cancer tumour recurrence more accurately.
Magnetic resonance imaging (MRI) holds great potential to spare men with suspected prostate cancer a painful biopsy. In our interview, Dr. Peter Seidensticker, Head of Medical Affairs Radiology at Bayer, outlines how MRI could be implemented as a first-line diagnostic.
Cardiac imaging is evolving, and new techniques continue to uncover the secrets of the heart for cardiologists who know how to use them. At the ESC 2025 Congress in Madrid, four experts explored cutting-edge developments across different modalities. Ranging from AI-assisted ultrasound image acquisition and accelerated MRI protocols to advanced prognostic tools for CT and nuclear imaging, these…
At the EANS neurosurgery congress in Vienna, Italian medical imaging company Esaote presented I-Genius, a new open MRI system designed to provide real time checks during glioma surgery.
Researchers have developed a machine learning algorithm that uses cardiac MRI images to help identify breast cancer patients who may be at risk of cardiotoxicity during cancer treatment. The research, led by cardiologist Dr Paaladinesh Thavendiranathan from Toronto General Hospital University Health Network, was presented at the European Society of Cardiology's Cardio-Oncology Conference in…
Gadolinium-based contrast agents enhance visibility but also pose a significant health risk. A new AI-powered virtual MRI imaging technique is designed to offer a safer diagnostic approach.
Medical imaging methods are often affected by background noise, which can obscure fine anatomical details. A new approach to solve this problem draws inspiration from quantum mechanics.
Denoising of diffusion-weighted MRI data creates sharper images – but does it actually lead to better diagnostic results? Researchers explored the impact of noise removal on detecting abnormalities.
Using cardiac MRI, researchers have found that long-term exposure to air pollution is associated with early signs of heart damage, according to a new study.
Analyzing heart imaging and a full spectrum of medical records, a new AI tool can reveal previously hidden information about a patient’s heart health, including predictions of sudden cardiac arrest.
An AI-assisted model can take low-quality MRI heart scans and turn them into high quality images, while reducing the time needed to scan the heart by about 90%.
MRI study of 802 patients shows carotid plaques become more complex over six years, with calcified plaques twice as likely to develop dangerous internal bleeding.
