HAMAM
Highly Accurate Breast Cancer Diagnosis through Integration of Biological Knowledge, Novel Imaging Modalities, and Modelling
| Coordinatore | EIBIR GEMEINNUETZIGE GMBH ZUR FOERDERUNG DER ERFORSCHUNG DER BIOMEDIZINISCHEN BILDGEBUNG
Organization address
address: Neutorgasse 9/2a contact info |
| Nazionalità Coordinatore | Austria [AT] |
| Totale costo | 4˙246˙965 € |
| EC contributo | 3˙099˙723 € |
| Programma | FP7-ICT
Specific Programme "Cooperation": Information and communication technologies |
| Code Call | FP7-ICT-2007-2 |
| Funding Scheme | CP |
| Anno di inizio | 2008 |
| Periodo (anno-mese-giorno) | 2008-09-01 - 2012-02-29 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
EIBIR GEMEINNUETZIGE GMBH ZUR FOERDERUNG DER ERFORSCHUNG DER BIOMEDIZINISCHEN BILDGEBUNG
Organization address
address: Neutorgasse 9/2a contact info |
AT (Vienna) | coordinator | 0.00 |
| 2 |
BOCA RATON COMMUNITY HOSPITAL, INC.
Organization address
address: 800 MEADOWS ROAD contact info |
US (BOCA RATON, FLORIDA) | participant | 0.00 |
| 3 |
CHARITE - UNIVERSITAETSMEDIZIN BERLIN
Organization address
address: Chariteplatz 1 contact info |
DE (BERLIN) | participant | 0.00 |
| 4 |
EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZURICH
Organization address
address: Raemistrasse contact info |
CH (ZUERICH) | participant | 0.00 |
| 5 |
FRAUNHOFER-GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V
Organization address
address: Hansastrasse contact info |
DE (MUENCHEN) | participant | 0.00 |
| 6 |
MEVIS MEDICAL SOLUTIONS AG
Organization address
address: UNIVERSITAETSALLEE 29 contact info |
DE (BREMEN) | participant | 0.00 |
| 7 |
STICHTING KATHOLIEKE UNIVERSITEIT
Organization address
address: Comeniuslaan contact info |
NL (NIJMEGEN) | participant | 0.00 |
| 8 |
UNIVERSITY COLLEGE LONDON
Organization address
address: Gower Street contact info |
UK (LONDON) | participant | 0.00 |
| 9 |
UNIVERSITY OF DUNDEE
Organization address
address: Nethergate contact info |
UK (DUNDEE) | participant | 0.00 |
Mappa
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Obiettivo del progetto (Objective)
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.