An algorithm did better than experts radiologists at finding tiny brain hemorrhages in head scans — an advance that one day may help doctors treat patients with strokes.
Machine learning has the potential to vastly advance medical imaging, particularly CT scanning, by reducing radiation exposure and improving image quality.
Researchers announce critical advances in the use of 3D-printed coronary phantoms with diagnostic software, further developing a non-invasive diagnostic method for Coronary Artery Disease risk assessment.
Patients could soon get faster and more accurate diagnoses with new software that can automatically detect signs of diabetes, heart disease and cancer from medical images.
Researchers have developed a system using artificial intelligence to quickly diagnose and classify brain hemorrhages and to provide the basis of its decisions from relatively small image datasets.
Researchers have developed a new technique of external ventricular drain insertion that involves the use of a mixed-reality holographic computer headset.
Machine learning has detected one of the commonest causes of dementia and stroke, in CT brain scans, more accurately than current methods.
VR brings medical images to life on screen, showing interventional radiologists a patient’s unique internal anatomy to help physicians effectively prepare and tailor their approach to complex treatments.