Computational multifocal microscopy

TL;DR

This paper introduces a simplified computational framework for high-resolution 3D microscopy using a single diffractive optical element, enabling real-time 3D imaging with improved resolution and minimal system complexity.

Contribution

The authors develop a unified computational approach with a redesigned optical setup that achieves high-resolution 3D imaging without empirical parameter tuning.

Findings

Achieved lateral resolution of 0.35um and axial resolution of 0.5um.

Recorded 3D videos of moving bacteria at 25 fps.

Simplified optical setup with only one additional grating.

Abstract

Despite recent advances, high performance single-shot 3D microscopy remains an elusive task. By introducing designed diffractive optical elements (DOEs), one is capable of converting a microscope into a 3D "kaleidoscope", in which case the snapshot image consists of an array of tiles and each tile focuses on different depths. However, the acquired multifocal microscopic (MFM) image suffers from multiple sources of degradation, which prevents MFM from further applications. We propose a unifying computational framework which simplifies the imaging system and achieves 3D reconstruction via computation. Our optical configuration omits chromatic correction grating and redesigns the multifocal grating to enlarge the tracking area. Our proposed setup features only one single grating in addition to a regular microscope. The aberration correction, along with Poisson and background denoising, are incorporated in our deconvolution-based fully-automated algorithm, which requires no empirical parameter-tuning. In experiments, we achieve the spatial resolutions of $0.35$um (lateral) and $0.5$um (axial), which are comparable to the resolution that can be achieved with confocal deconvolution microscopy. We demonstrate a 3D video of moving bacteria recorded at $25$ frames per second using our proposed computational multifocal microscopy technique.