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HyPPOCRATES

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Medical Hyperspectral Image and Video Processing and Interpretation via Constrai...

Medical Hyperspectral Image and Video Processing and Interpretation via Constrained Matrix and Tensor Factorization 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 informatio... ver más

06/10/2022

NATIONAL OBSERVATO...

260K€

Presupuesto del proyecto: 260K€

Líder del proyecto

ETHNIKO ASTEROSKOPEIO ATHINON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-10-06

MSCA-IF-2018: Individual Fellowships

I+D

Cerrada hace 6 años

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

3 Participantes

NATIONAL OBSERVATORY OF ATHE...

259.81K€ | Lider

JOHNS HOPKINS UNIVERSITY

177.27K€ | Participante

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Duración del proyecto: 42 meses Fecha Inicio: 2019-03-27
Fecha Fin: 2022-10-06

Líder del proyecto

ETHNIKO ASTEROSKOPEIO ATHINON No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 260K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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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