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QUSTom

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Quantitative Ultrasound Stochastic Tomography - Revolutionizing breast cancer di...

Quantitative Ultrasound Stochastic Tomography - Revolutionizing breast cancer diagnosis and screening with supercomputing-based radiation-free imaging. Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human t... ver más

30/09/2024

BARCELONA SUPERCOM...

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

BARCELONA SUPERCOMPUTING CENTERCENTRO NACIONA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5 | 118M€

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-09-30

HORIZON-EIC-2021-PATHFINDEROPEN-01-01: EIC Pathfinder Open 2021 Scope:You should apply to this call if you are looking for support from EIC Pathfinder Open to reali...

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6 Participantes

BARCELONA SUPERCOMPUTING CEN...

737.30K€ | Lider

FRONTWAVE IMAGING

427.38K€ | Participante

ARCTUR COMPUTER ENGINEERING

204.00K€ | Participante

IMPERIAL COLLEGE OF SCIENCE...

N.D. | Participante

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Duración del proyecto: 29 meses Fecha Inicio: 2022-04-21
Fecha Fin: 2024-09-30

Líder del proyecto

BARCELONA SUPERCOMPUTING CENTERCENTRO NACIONA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5 | 118M€

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human tissue with very high resolution. At present time, such images can only be attained by means of high-performance computing and using specific ultrasound data acquisition devices. When combined, hardware and software have a huge impact potential for soft-tissue imaging, such as in breast cancer imaging. Nevertheless, and as is customary in medical imaging, the obtained images only provide with the mean, or most likely, values of tissue at each pixel, being uncertainty quantification an extremely expensive process, typically deemed as unfeasible for practical purposes. A revolutionary development in adjoint-based ultrasound imaging allows us to potentially obtain images of uncertainties at the cost of a single, mean-value, image. Such development will be the basis of transformative implications in terms of confidence-estimates for diagnosis. We aim at disrupting the breast cancer screening paradigm by means of a safe (radiation-free), accurate (quantitative) and reliable (uncertainty-aware) novel breast imaging modality. Within QUSTom we will investigate the fundamental science behind adjoint-based uncertainty imaging and establish its potential suitability for breast cancer diagnosis. The feasibility of the technology as a diagnosis tool relies on 1) adapting the data acquisition hardware for optimal resolution, 2) implementing the algorithms in high-performance computers in order to obtain a short time-to-solution and 3) feasibility analysis by expert radiologists in comparison with the state-of-the-art in breast imaging. This proposal covers the three aspects and opens the possibility of applying similar principles in other imaging fields, both in medicine and elsewhere.

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