Medical Imaging

The FDA has granted 510(k) clearance for technology that uses AI to enhance images from shorter scan procedures.

Cardiologs co-founder and CEO Yann Fleureau was named the European Innovator of the Year by MIT Technology Review, which also included the French native on its list of the top 35 European innovators under the age of 35.

The FDA is speeding up the review process for new software that uses AI to help radiologists diagnose chronic thromboembolic pulmonary hypertension (CTEPH), pharmaceutical company Bayer announced Dec. 3.

NYU Langone Health’s Department of Radiology is planning to release a large-scale dataset that includes more than 1.5 million MRI knee images in an ongoing effort to make MRI scans faster with AI.

A deep-learning algorithm was significantly faster and just as accurate as most radiologists in analyzing chest X-rays for several diseases, according to a study led by Stanford University researchers.

With the help of machine learning, researchers were able to train a computer to analyze breast cancer images and classify tumors accurately, according to a study published in NPJ Breast Cancer.

After receiving FDA clearance for AI software that can detect brain bleeds from CT images, MaxQ AI has announced a deal to integrate the software with medical imaging platforms.

In an interview with AI in Healthcare, JingJia Liu, chief executive officer at Wision AI, discussed the company's new machine-learning algorithm for polyp detection, what’s next and the impact of AI products in the medical industry.

Five technology centers dedicated to using AI to speed up disease diagnosis and improve patient outcomes are opening throughout the United Kingdom.

NinePoint Medical, a Massachusetts-based medical device company, has received market clearance from the FDA for its new AI-based platform for image feature segmentation.

Researchers are hopeful a newly-developed machine-learning algorithm can be used to improve the detection of benign polyps during colonoscopies following a recent study validating the method.

A deep learning technique was able to detect glaucoma with more accuracy than traditional approaches, according to a recent study conducted by IBM and New York University scientists.