Radiology researchers have been spent countless hours seeking a dose-reduction technique that provides high-quality images while still limiting the patient’s exposure to ionizing radiation as much as possible.

Radiology researchers are turning to deep learning (DL) technology to make NLP even more effective—and it’s a growing trend that shows no signs of slowing down.  

Anyone looking to learn more about blockchain should keep these limitations in mind at all times.

AI is only going to be a true game-changer if it can work its magic with significant speed and efficiency.

Researchers have developed a new quantitative framework that evaluates thyroid nodules at a level comparable to two expert radiologists.

When research teams are developing deep learning models, they have to make certain decisions about the image resolutions used in their work. For instance, should they always aim to use the largest images possible? Or are there times when smaller images can get the job done?  

The rise of AI in healthcare—especially radiology—has launched countless conversations about ethics, bias and the difference between “right” and “wrong.”

Deep learning-based reconstruction (DLR) can reduce the radiation dose associated with low-dose chest and abdominal CT scans without sacrificing image quality, according to a new study published in the American Journal of Roentgenology.

The American Society of Radiologic Technologists (ASRT) has published a new white paper on AI and its potential impact on the work of medical imaging and radiation therapy professionals.

AI algorithms can improve the quality of brain MRI images, according to new findings published in Neurocomputing.