  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 reconstruct a Giga-voxel 4D hypercube in a fast manner while
only measuring 0.03 % of the information. 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.
