Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusion.

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.

Imaging the optical properties of turbid media with single-pixel detection based on the Kubelka-Munk model.

We present a diffuse optical imaging system with structured illumination and integrated detection based on the Kubelka-Munk light propagation model for the spatial characterization of scattering and absorption properties of turbid media. The proposed system is based on the application of single-pixel imaging techniques. Our strategy allows us to retrieve images of the absorption and scattering properties of a turbid media slab by using integrating spheres with photodiodes as bucket detectors. We validate our idea by imaging the absorption and scattering coefficients of a spatially heterogeneous phantom.