Project description
Computational specificity: AI tools for detecting inflammation in multiphoton imaging
Staining tissues enhances visualisation and helps scientists identify potential pathologies. Thereby, biochemical contrast agents bind to target molecules, which provides the desired specificity. Label-free multiphoton microscopy, on the other hand, is a powerful imaging technique to generate high-resolution 3D images in living tissue without use of stains or dyes. Modern AI tools can link the information in these label-free images to a given type of cell or tissue to generate computational specificity. With the support of the Marie Skłodowska-Curie Actions programme, the MICS project will develop such AI tools for digital staining of immune cells and automated classification of mucosal inflammation in multiphoton microscopy images. This will allow direct investigation of specific immune cell localisation and global tissue alteration.
Objective
Digital staining based on machine learning models can provide cellular specificity to label-free optical imaging. This concept is particularly interesting for in vivo applications in fundamental research of auto-immune diseases as well as for future clinical translations. In this project “MICS – Multiphoton imaging with computational specificity”, I will develop and implement computational specificity for label-free multiphoton microscopy (MPM) using artificial intelligence (AI). The direct outcome of this project will be two AI modules to perform (i) automated classification of mucosal inflammation based on 3D images from colon tissue and (ii) digital staining of un-stained immune cells. This integration of computational specificity to label-free multiphoton microscopy will allow direct investigation of global tissue alteration as well as specific immune cell localization during inflammatory tissue remodelling. Digital staining is an emerging concept in the field of computational microscopy but has not yet been implemented for immune cells based on label-free MPM images. Building on my previous expertise in label-free in vivo imaging via endomicroscopy, future implementations of multiphoton endomicroscopy would profit from tools for computational specificity, developed during this project.
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2022-PF-01
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91058 Erlangen
Germany
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