Hola,
¿eres nuevo aquí?

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

Tengo cuenta

Regístrate

Ver video

HAMAM

Financiado

Cerrado

Highly Accurate Breast Cancer Diagnosis through Integration of Biological Knowle...

Highly Accurate Breast Cancer Diagnosis through Integration of Biological Knowledge Novel Imaging Modalities and Modelling Despite tremendous advances in modern imaging technology, both early detection and accurate diagnosis of breast cancer are still unresolved challenges. Today, a variety of imaging modalities and image-guided biopsy procedures exis... ver más

29/02/2012

EIBIR GEMEINNUTZIG...

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

EIBIR GEMEINNUTZIGE GMBH ZUR FORDERUNG DER ER... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 10 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2012-02-29 No tenemos la información de la convocatoria

0% 73% 100%

Información adicional privada

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

10 Participantes

EIBIR GEMEINNUTZIGE GMBH ZUR...

0.00€ | Lider

UNIVERSITY COLLEGE LONDON

ETH Zürich

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

CADe4BMRI Improved detection and characterisation of breast cancer usi... 88K€ Cerrado

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

TIN2011-23704 M3CAD. MULTI-MODALITY AND MULTI-VIEW MAMMOGRAPHIC COMPUTER A... 15K€ Cerrado

SCARtool Scattered radiation reduction tool to improve computer aided... 158K€ Cerrado

PDC2022-133383-I00 PLATAFORMA POTENCIADA POR IA PARA EL DIAGNOSTICO DE SUBTIPOS... 129K€ Cerrado

MAMMOCARE Breast biopsy system guided by Positron Emission Mammography... 1M€ Cerrado

Líder del proyecto

EIBIR GEMEINNUTZIGE GMBH ZUR FORDERUNG DER ER... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Despite tremendous advances in modern imaging technology, both early detection and accurate diagnosis of breast cancer are still unresolved challenges. Today, a variety of imaging modalities and image-guided biopsy procedures exist to identify and characterize morphology and function of suspicious breast tissue. However, a clinically feasible solution for breast imaging, which is both highly sensitive and specific with respect to breast cancer, is still missing. As a consequence, unnecessary biopsies are taken and tumours frequently go undetected until a stage where therapy is costly or unsuccessful.HAMAM will tackle this challenge by providing a means to seamlessly integrate the available multi-modal images and the patient information on a single clinical workstation. Based on knowledge gained from a large multi-disciplinary database, populated within the scope of this project, suspicious breast tissue will be characterised and classified.HAMAM will achieve this by; Building the tools needed to integrate datasets / modalities into a single interface. Providing pre processing / standardization tools that will allow for optimal comparison of disparate data Building spatial correlation information datasets to allow for new similarity and multimodal tissue models. These will be key in the detection and diagnosis of breast cancer Building in adaptability that allows for the integration of other sources of knowledge such as tumour models, genetic data, genotype, phenotype and standardised imaging.The exact diagnosis of suspicious breast tissue is ambiguous in many cases. HAMAM will resolve this using the statistical knowledge extracted from the large case database. The clinical workstation will suggest additional image modalities that may be captured to optimally resolve these uncertainties. The workstation thus guides the clinician in establishing a patient specific optimal diagnosis. This ultimately leads to a more specific and individual diagnosis.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores