Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

QUSTom

Financiado

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€

Ver 6 Participantes

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...

I+D

Cerrada hace 3 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

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

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Proyectos interesantes

COMBIOSCOPY Computational Biophotonics for Endoscopic Cancer Diagnosis a... 1M€ Cerrado

TED2021-130081B-C21 A COMPREHENSIVE COMPUTER-AIDED DIGANOSIS (CAD) SYSTEM BASED... 193K€ Cerrado

PID2021-123390OB-C21 ENSAYOS CLINICOS VIRTUALES PARA ALGORITMOS DE IA EXPLICABLE... 185K€ Cerrado

Super-FALCON Super-resolution, ultrafast and deeply-learned contrast ultr... 2M€ Cerrado

EUIN2017-84904 DESARROLLO DE UN SISTEMA CAD BASADO EN BIOMARCADORES DE IMAG... 25K€ Cerrado

TIN2012-37171-C02-01 IA-BIOBREAST: ANALISIS TEMPORAL Y DETECCION AUTOMATICA DE LE... 33K€ Cerrado

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€

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.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores