  Fluorescence microscopy has been a significant tool to observe long-term
imaging of embryos (in vivo) growth over time. However, cumulative exposure is
phototoxic to such sensitive live samples. While techniques like light-sheet
fluorescence microscopy (LSFM) allow for reduced exposure, it is not well
suited for deep imaging models. Other computational techniques are
computationally expensive and often lack restoration quality. To address this
challenge, one can use various low-dosage imaging techniques that are developed
to achieve the 3D volume reconstruction using a few slices in the axial
direction (z-axis); however, they often lack restoration quality. Also,
acquiring dense images (with small steps) in the axial direction is
computationally expensive. To address this challenge, we present a compressive
sensing (CS) based approach to fully reconstruct 3D volumes with the same
signal-to-noise ratio (SNR) with less than half of the excitation dosage. We
present the theory and experimentally validate the approach. To demonstrate our
technique, we capture a 3D volume of the RFP labeled neurons in the zebrafish
embryo spinal cord (30um thickness) with the axial sampling of 0.1um using a
confocal microscope. From the results, we observe the CS-based approach
achieves accurate 3D volume reconstruction from less than 20% of the entire
stack optical sections. The developed CS-based methodology in this work can be
easily applied to other deep imaging modalities such as two-photon and
light-sheet microscopy, where reducing sample photo-toxicity is a critical
challenge.
