Numerically enhanced adaptive optics-based 3D STED microscopy for deep-tissue super-resolved imaging

Abstract

In stimulated emission depletion (STED) nanoscopy, the major origin of decreased signal-to-noise ratio within images can be attributed to sample photobleaching and strong optical aberrations. This is due to STED utilising both a high power depletion laser (increasing risk of photodamage), while the depletion beam is very sensitive to sample-induced aberrations. Here we demonstrate a custom-built 3D STED microscope with automated aberration correction that is capable of 3D super-resolution imaging through thick, highly aberrating, tissue. We introduce and investigate image denoising by block-matching and collaborative filtering (BM3D) to numerically enhance fine object details otherwise mixed with noise. Numerical denoising provides an increase in the final effective resolution of the STED imaging of 31% using the well-established Fourier ring correlation metric. Experimental validation of the proposed method is achieved through super-resolved 3D imaging of axons in differentiated induced pluripotent stem cells growing under a 80µm thick layer of tissue with lateral and axial resolution of 256nm and 300nm, respectively.

Automatic fringe pattern enhancement using truly adaptive period-guided bidimensional empirical mode decomposition

“…In these cases informative components are partially eliminated upon denoising due to lack of the noise itself. It suggests to use lower sigma (5)(6)(7)(8)(9)(10) in the cases of the detail-rich biological object study, like in QPI [61][62][63] or fluorescent microscopy [71]. Fig.…”