The amount of medical images is growing at a fast pace, as is their size and dimensionality. This puts pressure on the human experts who interpret the imagery while being fully liable and having to meet high compliance standards.
To help radiologists in their diagnoses, we collaborated with the National Institutes of Health of the USA, using deep learning-based image recognition to easily identify specific organs and detect any anomalies. Radiologists now rely on this software to interpret results, but also use it to produce summaries of scans out of huge amounts of data, all in a heartbeat.
We worked with Dr. Ronald Summers, recently named in the Top 100 AI pioneers in Healthcare by Forbes, presenting our research paper at the IEEE conference in Venice in April 2019. Why all the research? Aren’t we in the software business?
Certainly, but sharing knowledge and insights with other researchers in the field enables us to innovate even more quickly. We are hoping to improve healthcare for everyone, which is why we’ve prolonged our partnership with the NIH to develop an AI platform aimed at assisting in diagnoses by interpreting medical images.
