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

Area of Science:

• Biomedical Imaging
• Optics
• Data Science

Background:

• Time-resolved fluorescence imaging is crucial for non-invasive biomedical analysis.
• Large datasets in imaging present challenges for acquisition speed and processing.
• Existing methods struggle with the high data volume generated.

Purpose of the Study:

• To introduce a novel technique for fast giga-voxel 4D hypercube acquisition.
• To address the limitations of current time-resolved fluorescence imaging methods.
• To enable efficient collection and processing of complex imaging data.

Main Methods:

• A system combining two single-pixel cameras and a 2D array detector operating in parallel.
• Development of data fusion techniques to integrate data from multiple sensors.
• Acquisition of a 4D hypercube by measuring only 0.03% of the full dataset.

Main Results:

• Successful acquisition of a giga-voxel 4D hypercube with high resolution.
• Demonstration of a significantly reduced data measurement requirement.
• Validation of the technique's ability to capture detailed spectral and temporal signatures.

Conclusions:

• The novel technique offers a fast and efficient approach to time-resolved fluorescence imaging.
• Data fusion enables the reconstruction of high-resolution 4D hypercubes from sparse measurements.
• This method has potential for identifying fluorophore species based on their unique signatures.