Project description
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.
Objective
Routine radiology services are facing a huge problem on having efficient workflows to deliver X-ray analysis and diagnosis
shortly after image acquisition – with patients waiting days or weeks for the results. The volume of X-rays scans is quickly
growing year after year –more than 140 million X-rays analysis of the musculoskeletal (MSK) system were performed in
2018 in Europe alone. The current number of radiologists is insufficient to efficiently analyse and deliver the medical report
shortly, causing unnecessary stress for patients and potential delay in the treatment. Thus, there is an urgent need for
solutions optimizing the workflow on routine radiology services.
Radiobotics (RDB) has developed a comprehensive machine learning-based software tool that automatically analyses X-rays
of the MSK system and generates the respective medical report. The algorithms used have been trained with data
screened and validated by our clinical partners, in order to mimic expert accuracy and a state-of-the-art performance. RDB
automatic software will greatly benefit: 1) radiologists/physicians (end-users) by lowering the time required to analyse
images and generate diagnostic reports; 2) hospitals (customers) by optimizing the services workflow, saving costs and
offering higher quality services; and 3) patients by having access to a faster and accurate diagnosis and consequently early
treatments.
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 (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- medical and health sciences clinical medicine radiology
- engineering and technology medical engineering diagnostic imaging
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1263 Copenhagen
Denmark
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.