Project description DEENESFRITPL Machine learning supports radiology services The number of X-ray scans performed in Europe is increasing. In 2018, in the case of musculoskeletal (MSK) scans, the number exceeded 140 million. At the same time, a shrinking group of radiologists must deal with the increasing workflow. Consequently, medical reports cannot be ready in good time, and patient treatment is delayed. New solutions to support radiology services are therefore needed. The EU-funded AutoRay project aims to introduce to the medical market the Radiobotics (RDB) solution – a validated, comprehensive, ML-based software tool, which automatically analyses X-rays of the MSK system. The new software will help radiologists deliver fast and accurate analysis. It will also optimise the workflow in hospitals, lowering costs and improving the quality of services. Show the project objective Hide the project objective Objective Routine radiology services are facing a huge problem on having efficient workflows to deliver X-ray analysis and diagnosisshortly after image acquisition – with patients waiting days or weeks for the results. The volume of X-rays scans is quicklygrowing year after year –more than 140 million X-rays analysis of the musculoskeletal (MSK) system were performed in2018 in Europe alone. The current number of radiologists is insufficient to efficiently analyse and deliver the medical reportshortly, causing unnecessary stress for patients and potential delay in the treatment. Thus, there is an urgent need forsolutions optimizing the workflow on routine radiology services.Radiobotics (RDB) has developed a comprehensive machine learning-based software tool that automatically analyses X-raysof the MSK system and generates the respective medical report. The algorithms used have been trained with datascreened and validated by our clinical partners, in order to mimic expert accuracy and a state-of-the-art performance. RDBautomatic software will greatly benefit: 1) radiologists/physicians (end-users) by lowering the time required to analyseimages and generate diagnostic reports; 2) hospitals (customers) by optimizing the services workflow, saving costs andoffering higher quality services; and 3) patients by having access to a faster and accurate diagnosis and consequently earlytreatments.AutoRay project will enable RDB to mature its product to a market-ready software suite addressing multiple conditions in multiple anatomical regions while ensuring a seamless integration in IT systems. In addition, it will provide a stage to a large-scale demonstration of its performance in clinical practice. Upon completion, RDB will open up for a very large business opportunity, providing a perspective for RDB to become a lead player in the medical imaging arena. Fields of science natural sciencescomputer and information sciencessoftwaremedical and health sciencesclinical medicineradiologyengineering and technologymedical engineeringdiagnostic imaging Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-SMEInst-2018-2020 - SME instrument Call for proposal H2020-EIC-SMEInst-2018-2020 See other projects for this call Sub call H2020-EIC-SMEInst-2018-2020-3 Funding Scheme SME-2b - SME Instrument (grant only and blended finance) Coordinator RADIOBOTICS APS Net EU contribution € 1 333 816,05 Address Esplanaden 8c 1tv 1263 Copenhagen Denmark See on map Region Danmark Hovedstaden Byen København Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 571 635,45
