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EU funding (€3,875,953): ADAPTIVE OPTICAL METASURFACES FOR REAL-TIME, LABEL-FREE AND NON-DESTRUCTIVE 7D DIGITAL PATHOLOGY Hor8 Nov 2024 EU Research and Innovation programme "Horizon"
Overview
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ADAPTIVE OPTICAL METASURFACES FOR REAL-TIME, LABEL-FREE AND NON-DESTRUCTIVE 7D DIGITAL PATHOLOGY
Treatment decisions for many pathological conditions, including inflammatory, degenerative, autoimmune, infectious diseases, and cancer, are largely based on microscopy study of the surgically excised tissue specimens (histology). OPTIPATH provides a new paradigm for gathering objective optical tissue-dependent data, which is essential to overcoming the diagnostic challenges of inter-observer variability and limited sensitivity and specificity. OPTIPATH will offer non-destructive, label-free, real-time, 3D-presentation of tissue samples. This is enabled by (i) revolutionary nano-photonic optical metasurfaces (OMS) for simultaneous single-shot acquisition of spectral and polarimetric information, and adaptive OMS actuated by thin-film piezoelectric Micro-Electro-Mechanical-Systems (MEMS) for (ii) rapid Vector Vortex Beam (VVB) shaping of light, and (iii) rapid confocal 3D imaging. The wealth of objective diagnostic data provided will be interpreted using Machine Learning (ML) / Deep Learning (DL), and is essential to overcome inter-observer variability in diagnosis and provide actionable insights to the clinician. By utilizing optical markers present in unprepared tissue histological procedures can be dramatically sped up, offering real-time diagnosis in operation theatres and pathology departments. By offering timely and accurate diagnosis, OPTIPATH will enable early diagnosis and improved prognosis of recovery.
Funded Companies:
| Company name | Funding amount |
| Aston University | €466,290 |
| Idryma Technologias Kai Erevnas | €545,000 |
| NIL Technology ApS | €500,000 |
| Oslo Universitetssykehus HF | €0.00 |
| Oulun Yliopisto | €459,638 |
| Sintef AS | €953,875 |
| Syddansk Universitet | €601,150 |
| Universitetet I Oslo | €350,000 |
Source: https://cordis.europa.eu/project/id/101185769
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