Physics-Driven Zero-Shot Reconstruction of Isotropic 3D Fluorescence Microscopy under Undersampled Acquisition
Cao, R.; Jin, T.; Xin, F.; Hou, Y.; Fu, Y.; Jin, B.; Li, L.; Gao, S.; Wang, H.; Li, Y.; Saimi, D.; Ren, W.; Wang, W.; Xin, G.; Yuan, K.; Chen, Z.; Su, X.; Kim, D.; Li, M.; Xi, P.
Show abstract
Three-dimensional (3D) imaging represents the development of next generation of fluorescence microscopy. However, routine axial down-sampling makes isotropic resolution unrealistic. Here, we propose DeepUI, a physical zero-shot framework designed to achieve isotropic 3D fluorescence images from a low axial sampling rate. DeepUI fully leverages the intrinsic characteristics of 3D images through physics-guided degradation, which incorporates spatial-frequency joint learning to generate a scaled optical transfer function, combined with noise degradation and an up-sampling branch. Typically requiring just 5 minutes for training and 0.5 minutes for high-throughput and fast prediction, we demonstrate the superior performance of DeepUI to get isotropic results, and the exclusivity to axial down-sampling conditions, even in more challenging conditions, including defocused background, noise, and resolution blur.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.