IFLAI
Financiado
Virtual tissue staining by deep learning
Our goal is to create a virtual tissue-staining device to replace manual chemical-staining techniques by integrating optics and deep
learning.
Chemical staining of cell components plays an essential role in biomedical and pharmac...
Our goal is to create a virtual tissue-staining device to replace manual chemical-staining techniques by integrating optics and deep
learning.
Chemical staining of cell components plays an essential role in biomedical and pharmaceutical research and practice. Cell structures
of interest are highlighted using various chemical stains and imaged with the appropriate optical setup. However, these techniques
are often invasive and sometimes even toxic to the cells, in addition to being time consuming, labor intensive, and expensive.
Recently, the use of deep learning has been proposed as a way to create images of virtually stained cell structures, thus mitigating the
inherent problems associated with the conventional chemical staining. However, these methods are usually specialized for a specific
application and, thus, highly dependent on the setting of the optical device used for acquiring the training data.
In order to make virtual tissue-staining more accessible to end-users, we propose a device based on a simple optical system with an
integrated deep-learning-powered virtual-staining software.
This is an ideal moment to enter the virtual tissue-staining market because we can gain a first mover advantage. Further, we can take
advantage of the fact that the tissue-staining market is expected to grow with a compound annual rate of roughly 8.5% until 2025 (up
to 3400M USD), and to continue to grow for the foreseeable future.
As part of this project, we aim to launch the startup company IFLAI to commercially exploit our virtual-staining technology and the
prototype we will develop. With the startup IFLAI, we aim to provide ~20 jobs to university-educated individuals in the EU within the
next 5 years. IFLAI has already received initial funding and support from two different organisations that support and believe in its
venture.
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Duración del proyecto: 18 meses
Fecha Inicio: 2023-04-24
Fecha Fin: 2024-10-31
Fecha Fin: 2024-10-31
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-10-31
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2022-POC2:
ERC PROOF OF CONCEPT GRANTS2
Cerrada
hace 2 años
Presupuesto
El presupuesto total del proyecto asciende a
150K€
Líder del proyecto
GOETEBORGS UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5