The team’s work will emphasize the role of specialized MRI techniques capable of detecting subtle changes around tumors with the help of pH-based imaging.
Using a virtual reality headset, the system, dubbed AR-VIU (augmented real-time volumetric imaging in ultrasound), creates a 3D rendering of anatomy based on 2D ultrasound images.
A team of experts determined that correlating masses initially detected on MRI are significantly more likely to result in a cancer diagnosis than other common findings.
The model incorporates specific data from MRI exams with patient risk factors to predict whether a person is likely to develop clinically significant prostate cancer.
Finely tuned, pre-trained large language models are beginning to reliably translate image content into text, but are they ready to take on medical images?
Researchers tracked data from more than 400,000 patients for a new meta-analysis, presenting their findings in the Journal of the American Heart Association.
