Summary
Perception Ultrasound for Reassuring Fetal Echo Clinical Trainees (PURFECT) builds on the results of ERC Advanced Grant PULSE to develop an AI-assistive system to guide a user to find a standard mid-trimester fetal ultrasound imaging plane. Such a system would provide reassurance to newly qualified sonographers as they begin to perform real-world diagnostic imaging, may support experts perform scanning more efficiently, and would contribute to the desired trend to use ultrasound more widely in healthcare delivery.
The novelty of the proposed system is that the guidance provided by the PURFECT solution is provided by artificial intelligence (AI) multi-modal deep learning models which predict where an expert would look. These models have been built from ultrasound video and gaze tracking of full ultrasound scans as part of the PULSE project.
The Proof of Concept award aims to build on the algorithm research conducted in PULSE to systems engineer a working PURFECT prototype of an AI-assisted ultrasound image guidance system. This will require an inter-disciplinary approach to design, build and test a system suitable for use by the intended user. In addition to addressing the engineering challenges, the project will also conduct a series of pilot usability studies to understand how AI-assisted image plane guidance can assist a trainee in diagnostic imaging and give them reassurance just as a human tutor or more experienced colleague might do. The project aims to generate licensable intellectual property and therefore will consider as well commercialization options for the developed technology for post-project follow up.
The novelty of the proposed system is that the guidance provided by the PURFECT solution is provided by artificial intelligence (AI) multi-modal deep learning models which predict where an expert would look. These models have been built from ultrasound video and gaze tracking of full ultrasound scans as part of the PULSE project.
The Proof of Concept award aims to build on the algorithm research conducted in PULSE to systems engineer a working PURFECT prototype of an AI-assisted ultrasound image guidance system. This will require an inter-disciplinary approach to design, build and test a system suitable for use by the intended user. In addition to addressing the engineering challenges, the project will also conduct a series of pilot usability studies to understand how AI-assisted image plane guidance can assist a trainee in diagnostic imaging and give them reassurance just as a human tutor or more experienced colleague might do. The project aims to generate licensable intellectual property and therefore will consider as well commercialization options for the developed technology for post-project follow up.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/899742 |
| Start date: | 01-01-2021 |
| End date: | 31-12-2022 |
| Total budget - Public funding: | - 150 000,00 Euro |
Cordis data
Original description
Perception Ultrasound for Reassuring Fetal Echo Clinical Trainees (PURFECT) builds on the results of ERC Advanced Grant PULSE to develop an AI-assistive system to guide a user to find a standard mid-trimester fetal ultrasound imaging plane. Such a system would provide reassurance to newly qualified sonographers as they begin to perform real-world diagnostic imaging, may support experts perform scanning more efficiently, and would contribute to the desired trend to use ultrasound more widely in healthcare delivery.The novelty of the proposed system is that the guidance provided by the PURFECT solution is provided by artificial intelligence (AI) multi-modal deep learning models which predict where an expert would look. These models have been built from ultrasound video and gaze tracking of full ultrasound scans as part of the PULSE project.
The Proof of Concept award aims to build on the algorithm research conducted in PULSE to systems engineer a working PURFECT prototype of an AI-assisted ultrasound image guidance system. This will require an inter-disciplinary approach to design, build and test a system suitable for use by the intended user. In addition to addressing the engineering challenges, the project will also conduct a series of pilot usability studies to understand how AI-assisted image plane guidance can assist a trainee in diagnostic imaging and give them reassurance just as a human tutor or more experienced colleague might do. The project aims to generate licensable intellectual property and therefore will consider as well commercialization options for the developed technology for post-project follow up.
Status
CLOSEDCall topic
ERC-2019-POCUpdate Date
27-04-2024
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