Abstract

Time-resolved fluorescence imaging is a key tool in biomedical applications, as it allows to non-invasively obtain functional and structural information. However, the big amount of collected data introduces challenges in both acquisition speed and processing needs. Here, we introduce a novel technique that allows to acquire a giga-voxel 4D hypercube in a fast manner while measuring only 0.03% of the dataset. The system combines two single-pixel cameras and a conventional 2D array detector working in parallel. Data fusion techniques are introduced to combine the individual 2D and 3D projections acquired by each sensor in the final high-resolution 4D hypercube, which can be used to identify different fluorophore species by their spectral and temporal signatures.

© 2021 Optical Society of America

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Supplementary Material (2)

NameDescription
» Supplement 1       Revised supplement text.
» Visualization 1       4D recovery using data fusion techniques.

Data Availability

Analysis codes and an example low resolution 4D dataset can be found in [18]. Full resolution datasets are not publicly available at this time but may be obtained from the authors upon reasonable request.

18. F. Soldevila, A. Lenz, A. Ghezzi, A. Farina, C. D’Andrea, and E. Tajahuerce, “Single-pixel based Data Fusion algorithm for spectral-temporal-spatial reconstruction, ” Single-pixel 4d data fusion, 21 July 2021, https://github.com/cbasedlf/SinglePixelDataFusion4D.

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