What are the benefits of using an AI server downstream of PACS?

CHICAGO -- Among the imaging informatics sessions at RSNA 2023 are innovations designed to reduce the barriers of running AI algorithms in everyday radiology. To that end, research at the University of Pennsylvania suggests starting with an AI server. “For radiologists, we need AI to be fast … unobtrusive … and verifiable. We want AI results ready by the time we open a study,” explained presenter Neil Chatterjee, MD, PhD. “From the IT or enterprise point of view, we want AI that is secure,” he said, emphasizing fast outputs, smooth integration, and adhering to standards such as DICOM and HL7.Neil Chatterjee, MD, PhD.“There is quite a big gap between the amount of AI we see everywhere around us and the relatively small amount we use day to day,” he noted. “We think part of that is because it can be difficult to find AI that meets the needs both of the radiologists that use it every day and the needs of the larger IT enterprise.”In search of a win-win for AI in everyday use in radiology, Chatterjee and colleagues chose to narrow their proof-of-concept study to CT. He explained that with completed imaging an HL7 message is sent to the vendor neutral archive which triggers the PACS to send appropriate imaging data to the AI server that then treats the imaging studies with selected algorithms.Downstream of PACS, the AI server exports quality control images back to the PACs for radiologists' review as well as sends AI results to the reporting engine, Chatterjee ...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Enterprise Imaging PACS/VNA RSNA 2023 Source Type: news