Single-shot 3D wide-field fluorescence imaging with a Computational Miniature Mesoscope

Abstract

Fluorescence microscopes are indispensable to biology and neuroscience. The need for recording in freely behaving animals has further driven the development in miniaturized microscopes (miniscopes). However, conventional microscopes/miniscopes are inherently constrained by their limited space-bandwidth product, shallow depth of field (DOF), and inability to resolve three-dimensional (3D) distributed emitters. Here, we present a Computational Miniature Mesoscope (CM2) that overcomes these bottlenecks and enables single-shot 3D imaging across an 8 mm by 7 mm field of view and 2.5-mm DOF, achieving 7-μm lateral resolution and better than 200-μm axial resolution. The CM2 features a compact lightweight design that integrates a microlens array for imaging and a light-emitting diode array for excitation. Its expanded imaging capability is enabled by computational imaging that augments the optics by algorithms. We experimentally validate the mesoscopic imaging capability on 3D fluorescent samples. We further quantify the effects of scattering and background fluorescence on phantom experiments.

GEOMScope: Large Field‐of‐View 3D Lensless Microscopy with Low Computational Complexity

“…Compared to conventional cameras and microscopes where there is a one‐to‐one pixel mapping between the object plane and the sensor through the bulk lenses, lensless imagers map a single voxel in 3D objects to multiple pixels on a 2D camera through a thin piece of optics. [ 10,11,13–17,32–34 ] Depending on the imaging optics, which fundamentally determines the measurement matrix from object to image, there have been two major classes of lensless cameras reported (Table S1, Supporting Information). The first class is amplitude mask.…”

“…Its major drawback is the low light throughput and high sensitivity to alignment between the mask and the camera. The second class, which uses a phase mask such as a diffuser [ 10,17,38 ] or a microlens array, [ 13,14,16,39,40 ] increases the light throughput. Diffusers have a dense PSF requiring large spatial support, and it is not suitable for pixel back projection.…”

“…Lensless imaging devices [ 10–21 ] replace the bulk lenses in conventional imaging systems by a thin amplitude or phase mask [ 10–18 ] and enable compact 3D imaging through single exposure. However, they face challenges on the expensive computational cost in object reconstruction and tradeoffs among reconstruction quality, speed, and volume.…”

Three basic types of fluorescence microscopy and recent improvement

“…Gustafsson et al [4] applied structured illumination microscopy in 3D and doubled the 3D resolution in WF microscope. Xue et al applied Computational Miniature Mesoscope (CM2) to the wide-field microscope and successfully presented 3D imaging [12]. By using computational algorithms, they augmented the optics and expanded imaging capability.…”

Deep learning-based scattering removal of light field imaging

“…Especially, the LF imaging method based on the wave-optics model and LF point spread function (LFPSF) allows 3D deconvolution for the high-quality single-shot volumetric reconstruction [6,7] . However, in some applications of LF imaging, a scattering medium is present in the scenes, such as biological tissue, fog, and turbid water [8][9][10][11][12][13][14][15][16] . In these imaging scenes, signal light could still be captured, and 3D reconstruction could be conducted, but scattered light produced by the scattering medium introduces blur and scattering background artifacts to the 3D reconstruction image, which lead to low resolution and low contrast.…”