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HypErspectraL Imaging Cancer Detection

HypErspectraL Imaging Cancer Detection

Objective

Starting with some specific types of cancers, this project will try to generalize the methodology to discriminate between healthy and malignant tissues in real-time during surgical procedures. Using the hyperspectral signatures of the healthy tissues and the same tissues affected by cancer, a mathematical model of how cancer affects to the hyperspectral signature will be derived. The research will start with the challenging task of brain cancer detection. A precise resection of the gliomas will minimize the negative effect of removing brain cells while assuring an effective tumour resection. The second type of tumours to be analysed will be the lung and breast cancers as they represent the two most common cancers in the world. Based on the experience gained during the evolution of the project and guided by the oncologist expertise, many other types of cancer out from the more than 200 that affect human beings will be studied. As cancer supposes a change in the cellular physiology, it should be detected as a change in the hyper-spectral signature. This project will try to determine if there is a certain pattern that could be identified as a cancer hyperspectral signature. Although previous works demonstrates that hyperspectral imaging can be used for certain cancer detection in animals, no application to human beings in real-time surgery has been found. This project will develop an experimental intraoperative setup based on non-invasive hyperspectral cameras connected to a platform running a set of algorithms capable of discriminate between healthy or pathological tissues. This information will be provided, through different display devices to the surgeon, overlapping normal viewing images with simulated colours that will indicate the cancer probability of the tissue presently exposed during every instant of the surgical procedure. A high-efficiency hardware/software prototype will be developed with the aim of recognising cancer tissues on real time.

Coordinator

UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA

Address

C/ Juan De Quesada 30
35001 Las Palmas De Gran Canaria

Spain

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 145 367

Administrative Contact

Gustavo Marrero Callico (Dr.)

Participants (9)

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MEDTRONIC IBERICA SA

Spain

EU Contribution

€ 59 624

FUNDACION CANARIA DE INVESTIGACION Y SALUD

Spain

EU Contribution

€ 70 988

UNIVERSIDAD POLITECNICA DE MADRID

Spain

EU Contribution

€ 127 993

GENERAL EQUIPMENT FOR MEDICAL IMAGING SA

Spain

EU Contribution

€ 117 744

ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS

France

EU Contribution

€ 97 156

VIRTUAL ANGLE BV

Netherlands

EU Contribution

€ 126 080

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

United Kingdom

EU Contribution

€ 128 082

UNIVERSITY HOSPITALS SOUTHAMPTON NHS FOUNDATION TRUST

United Kingdom

EU Contribution

€ 95 602

ECOLE NATIONALE SUPERIEURE DES MINES DE PARIS

France

EU Contribution

€ 24 122

Project information

Grant agreement ID: 618080

Status

Closed project

  • Start date

    1 January 2014

  • End date

    31 December 2016

Funded under:

FP7-ICT

  • Overall budget:

    € 1 375 838

  • EU contribution

    € 992 758

Coordinated by:

UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA

Spain

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