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HyPPOCRATES SIGNED

Medical Hyperspectral Image and Video Processing and Interpretation via Constrained Matrix and Tensor Factorization

Total Cost €

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EC-Contrib. €

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Partnership

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Project "HyPPOCRATES" data sheet

The following table provides information about the project.

Coordinator
ETHNIKO ASTEROSKOPEIO ATHINON 

Organization address
address: LOFOS NYMFON
city: ATHINA
postcode: 11810
website: www.noa.gr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Greece [EL]
 Total cost 259˙808 €
 EC max contribution 259˙808 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-GF
 Starting year 2019
 Duration (year-month-day) from 2019-10-07   to  2022-10-06

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ETHNIKO ASTEROSKOPEIO ATHINON EL (ATHINA) coordinator 259˙808.00
2    JOHNS HOPKINS UNIVERSITY US (BALTIMORE) partner 0.00

Map

 Project objective

Over the past few years hyperspectral (HS) imaging has been broadly applied in a wealth of different applications with remote sensing of the environment being the most prominent one. HS imaging provides a rich amount of information by generating images and videos of high spectral resolution captured at a wide range of the electro-magnetic spectrum. Recently, HS data have been shown to offer remarkable advances to a new field of significant interest i.e., medical HS (mHS) imaging. The high spectral resolution of HS data makes them amenable to identifying even subtle spectral differences related to various pathological conditions. In view of that, mHS images and videos have received considerable attention lately. mHS data have already been used for non-invasive diagnosis of several types of cancer e.g. brain, tongue cancer, as well as for diabetic foot diagnosis and surgical guidance. mHS imaging is anticipated to remarkably flourish in the years to come taking into account the recent advances that have occurred in the development of micro-size and low-cost HS cameras. However, despite this large progress in HS imaging hardware, sophisticated algorithms capable to interpret these data are still missing. HyPPOCRATES aims at deriving new powerful mHS image and video interpretation schemes tailored to mHS data processing, by applying novel machine learning ideas. To this end, the problems of subspace clustering and unmixing will be investigated for performing refined mHS image and video understanding. Along those lines, constrained matrix and tensor factorization approaches will be explored for devising computationally efficient and scalable machine learning algorithms. Overall, the main objective of the project is to bridge the gap between the recent advances in mHS imaging and those in machine learning research. This way, the researcher aspires to go the diagnostic process of several serious diseases, such as various types of cancer, one step further.

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The information about "HYPPOCRATES" are provided by the European Opendata Portal: CORDIS opendata.

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