Hola,
¿eres nuevo aquí?

Registrate y conecta tu empresa con financiación pública, partners y proyectos.

CyberScoPy

Financiado

Smart, Event-Based Microscopy for Cell Biology

Timelapse fluorescence microscopy imaging is routinely used in quantitative cell biology. However, microscopes are passive systems and are still very limited in their operating capacity which limits in several ways our ability to... ver más

31/03/2025

CNRS

150K€

Presupuesto del proyecto: 150K€

Líder del proyecto

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 1 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-09-12

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2023-POC: ERC PROOF OF CONCEPT GRANTS

I+D

Cerrada hace 1 año

0% 100%

1 Participantes

CNRS

150.00K€ | Lider

Proyectos interesantes

SelfDriving4DSR Enabling Live Cell 4D Super Resolution Microscopy Guided by... 2M€ Cerrado

PID2021-126701OB-I00 METODOS DE VISION ARTIFICIAL EN ENTORNOS DE POCAS ANOTACIONE... 102K€ Cerrado

LowLiteScope A light-efficient microscope for fast volumetric imaging of... 150K€ Cerrado

MicroBeaCh Microfluidic Platform for Analyzing Sperm Flagellar Beating... 196K€ Cerrado

CSIC10-1E-924 Software Especializado de Análisis de Imágenes de Microscopí... 60K€ Cerrado

UNLC13-1E-2399 Laboratorio de imagen médica 12K€ Cerrado

Últimas noticias

27-11-2024: DGIPYME En las últimas 48 horas el Organismo DGIPYME ha otorgado 1 concesiones

27-11-2024: FUNDACION-EOI En las últimas 48 horas el Organismo FUNDACION EOI ha otorgado 2 concesiones

25-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 52 concesiones

Duración del proyecto: 18 meses Fecha Inicio: 2023-09-12
Fecha Fin: 2025-03-31

Presupuesto del proyecto 150K€

Descripción del proyecto Timelapse fluorescence microscopy imaging is routinely used in quantitative cell biology. However, microscopes are passive systems and are still very limited in their operating capacity which limits in several ways our ability to identify and image complex biological events in real time and at the proper 4D scales. They could become much more powerful investigation systems for the life science if they were endowed with user-friendly, unsupervised decision-making algorithms, transforming microscopes into fully responsive and automated measurement devices. Indeed, we are at a moment when smart systems and artificial intelligence are being used everywhere, including in laboratories to improve the functioning of many (scientific), however outdated preprogrammed microscopy workflows are still being routinely implemented. The ability to employ real-time image analysis to inform, optimize and adjust the settings of ongoing image acquisitions would be a game changer for studying complex, dynamic cellular processes. To address this issue, we have developed a pilot software, CyberSco.Py, which enables the possibility to conduct image analysis in real time (using deep learning) to trigger modifications in the acquisition settings thus alleviating the need for manual input and supervision. This allows for the implementation of novel classes of experiments that cannot be achieved with current solutions. Within the context of this PoC, CyberSco.Py will be developed into a user-friendly software capable of smart automation of microscopy systems an their add-ons (e.g. microfluidics, temperature controls, etc...). As such, CyberSco.Py has the potential to revolutionize the power and scope of microscopy experiments for quantitative cell biology with broad implications for the microscopy sector.

Conecta tu I+D

Entra hoy

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores