HAMAM

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 (Highly accurate breast cancer diagnosis through integration of biological knowledge, novel imaging modalities, and modelling) project 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.

For further information, please visit:
http://www.hamam-project.eu

Project co-ordinator:
EIBIR gemeinnuetzige GmbH zur Foerderung der. Erforschung der biomedizinischen Bildgebung

Partners:

  • Boca Raton Community Hospital Inc (USA)
  • MeVis Research GmbH (Germany)
  • MeVis Medical Solutions AG (Germany)
  • University College London (United Kingdom)
  • Radboud Universiteit Nijmegen - Stichting Katholieke Universiteit (Netherlands)
  • Charité - Universitätsmedizin Berlin (Germany)
  • The University of Dundee (United Kingdom)
  • Eidgenössische Technische Hochschule Zürich (Switzerland)

Timetable: from 09/2008 - to 08/2011

Total cost: € 4.250.000

EC funding: € 3.100.000

Programme Acronym: FP7-ICT

Subprogramme Area: Virtual physiological human

Contract type: Collaborative project (generic)


Related news article:

Most Popular Now

MSD Innovation Factory Selects 3 Compani…

Throughout the MSD Innovation Factory, MSD launched 7 health-related challenges to award the three most outstanding solutions. Blendarsys, Symptoma and Grupo Pulso are the winners out of 100 proposals. The...

Using Virtual Reality to Identify Brain …

Virtual reality is helping neuroscientists at the University of California, Davis, get new insight into how different brain areas assemble memories in context. In a study published Jan. 18 in...

People with Tetraplegia Gain Rapid Use o…

For a brain-computer interface (BCI) to be truly useful for a person with tetraplegia, it should be ready whenever it's needed, with minimal expert intervention, including the very first time...

East Lancashire Hospitals Chooses Cerner…

East Lancashire Hospitals NHS Trust (ELHT) has chosen global health information technology leader Cerner as its Preferred Supplier of a new clinical information system that will help to improve the...

Hamlyn Centre Announces Grant from Bill …

The Hamlyn Centre at Imperial College London today announces the award of a grant from the Bill & Melinda Gates Foundation, to accelerate research into new integrated technology systems for...

Philips Debuts Fully Integrated Suite o…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, announced the launch of its next-generation Patient Monitoring solution in the U.S. The enterprise-wide system consists of bedside...

Liverpool Awards Contract to Docobo

One of the best-known users of telehealth in England has awarded a contract to Docobo to significantly expand its service over the next three years. NHS Liverpool Clinical Commissioning Group...

Augmented Reality System Lets Doctors Se…

New technology is bringing the power of augmented reality into clinical practice. The system, called ProjectDR, allows medical images such as CT scans and MRI data to be displayed directly...

Assessing Health Technology in the EU: C…

European Commission has put forward a proposal to boost cooperation amongst EU Member States for assessing health technology. Greater transparency will empower patients, by ensuring their access to information on...

ProEmpower Releases Call for Tenders to …

The ProEmpower procurers are looking for a diabetes management solution that will tackle the unmet needs in the current treatment of diabetes such as the fragmentation in today’s healthcare systems...

Biosensors Will Be Inexpensive, Do More…

When it comes to biometric sensors, human skin isn't an ally. It's an obstacle. The University of Cincinnati is developing cutting-edge methods to overcome this barrier without compromising the skin...