Three-dimensional block-based restoration integrated with wide-field fluorescence microscopy for the investigation of thick specimens with spatially variant refractive index.
Development of a block-based restoration (BBR) method that addresses spatially variant (SV) imaging in wide-field fluorescence microscopy of thick samples is presented. The BBR method is based on a block-based imaging model, which approximates SV imaging using an efficient orthonormal basis decomposition of multiple SV point-spread functions computed at block vertices. The effect of reducing the number of blocks needed to account for SV imaging on the restoration accuracy was investigated with simulations using a numerical lung tissue phantom relevant to biological studies. Results show that reducing the number of blocks by 82% and 98% resulted in a 19% and 27% reduction in restoration accuracy, respectively, thereby establishing a reasonable tradeoff between computational resources and accuracy. Comparison of the BBR method to existing methods (deconvolution) that do not account for SV imaging demonstrates a 90% improvement in restoration accuracy. BBR results from synthetic and experimental images of a controlled test sample with SV refractive index (RI) show consistency, providing a validation of the BBR approach. In this study, information from DIC and fluorescence images was combined to identify regions with changing RI within the imaging volume. The BBR method provides a first step toward computationally tractable reconstruction of images from thick samples.
Sreya
S
Ghosh
Chrysanthe
C
Preza
D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008168:Lung / Q000737:chemistry; D008856:Microscopy, Fluorescence / Q000379:methods*; D008954:Models, Biological; D019047:Phantoms, Imaging; D012031:Refractometry / Q000379:methods*