Objective
Routine radiology services are facing a huge problem delivering analysis of the very large number of X-ray images shortly after acquisition – leading to patients sometimes waiting for weeks for the results. 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 diagnosis and treatment.
Radiobotics is developing a machine learning-based software that automatically analyses routine X-rays of the musculoskeletal system and generates the respective medical report. Although the recent advances in machine learning have accelerated the development of tools for medical imaging analysis, the solutions available are only semi-automatic and focused on other more acute and specific diagnoses. Radiobotics automatic software will decrease time use and improve diagnostic quality, greatly benefiting: 1) radiologists/physicians by lowering the amount of images queued up for analysis and increase the diagnostic volume that radiologists can deliver, while providing a more objective analysis; 2) hospitals/clinics/radiology centres by optimizing their workflow, saving costs and offering higher quality services to patients; and 3) patients by having access to a faster and accurate diagnosis and consequently early treatments.
AutoRay project will enable maturing our technology to a market-ready software and also to implement an effective business and communication strategy to build market awareness, and customer trust. We are supported by clinical development partners in Denmark and UK, and our team has the right combination of expertise in biomedical engineering, machine learning, business development and commercialization to perform this project and fulfil all the needs and requests of end-users and customers, eventually benefiting the society as whole.
Fields of science
- medical and health sciencesmedical biotechnology
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- medical and health sciencesclinical medicineradiology
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
1263 Copenhagen
Denmark
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.