AI-enhanced rapid lifetime determination method for fast macroscopic and mesoscopic fluorescence lifetime imaging (Conference Presentation)
Fluorescence lifetime imaging (FLI) offers several advantages, including the quantitative imaging of unique biosignatures in biological tissues, studies of drug-target interactions, and tumor margin identification. However, its adoption in surgical environments has been hindered by the time-consuming data acquisition and processing pipeline. In this work, we present an AI-enhanced rapid lifetime determination (RLD) method utilizing the SwissSPAD3 (SS3) detector, capable of acquiring a single frame to generate a large area FLI map. This method has been validated using fluorescence inclusions in tissue-mimicking phantoms, paving the way for complex in-vivo imaging. In conclusion, the AI-enhanced single-shot fluorescence lifetime estimation using the SwissSPAD3 detector represents a significant advancement in the RLD method, with promising potential for fluorescence-guided surgical applications.
Authors
- Xavier Intes (ORCID: https://orcid.org/0000-0001-5868-4845)
- Stefan T. Radev (ORCID: https://orcid.org/0000-0002-6702-9559)
- İsmail Erbaş (ORCID: https://orcid.org/0000-0002-1104-8670)
- Edoardo Charbon (ORCID: https://orcid.org/0000-0002-0620-3365)
- Luis Chavez (ORCID: https://orcid.org/0000-0002-4915-9632)
- Xavier Michalet (ORCID: https://orcid.org/0000-0001-6602-7693)
- Claudio Bruschini (ORCID: https://orcid.org/0000-0002-6636-6596)
- Margarida Barroso (ORCID: https://orcid.org/0000-0002-0407-3181)
- Vikas Pandey (ORCID: https://orcid.org/0000-0001-5477-1095)
Publication Details
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1117/12.3043294
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00