1 Mar 2018
16:00 — 16:30
Promising forecasts for the use of artificial intelligence in medical image analysis are based on various developments: The pressure on radiologists is growing due to the rising use of imaging methods with increased complexity. On the other hand, health care costs are on the rise due to various factors. Process optimization in medicine is therefore necessary to counteract this development. In particular, images from magnetic resonance imaging (MRI) and computer tomography (CT) can be diagnosed faster and more reliably by computer intelligence than by radiologists alone. In order to achieve a high level of acceptance for these new solutions among physicians, it is necessary to focus on the process chain and offer the physician additional benefits. Using the example of the assisted diagnosis of prostate carcinoma with Deep Learning procedures, we want to demonstrate such a procedure and also briefly address the aspects of data protection and possible business models.