Abstract
Light field microscopy (LFM) has been widely used for recording 3D biological dynamics at camera frame rate. However, LFM suffers from artifact contaminations due to the illness of the reconstruction problem via naïve Richardson–Lucy (RL) deconvolution. Moreover, the performance of LFM significantly dropped in low-light conditions due to the absence of sample priors. In this paper, we thoroughly analyze different kinds of artifacts and present a new LFM technique termed dictionary LFM (DiLFM) that substantially suppresses various kinds of reconstruction artifacts and improves the noise robustness with an over-complete dictionary. We demonstrate artifact-suppressed reconstructions in scattering samples such as Drosophila embryos and brains. Furthermore, we show our DiLFM can achieve robust blood cell counting in noisy conditions by imaging blood cell dynamic at 100 Hz and unveil more neurons in whole-brain calcium recording of zebrafish with low illumination power in vivo.
Highlights
Cellular motions and activities in vivo are usually in millisecond time-scale and in 3D space, including voltage and calcium transients of neurons[1,2], blood cell flows in beating hearts[3], and membrane dynamics in embryo cells[4]
We argue that such contrast increase is at the cost of image structure distortions, which should be alleviated for quantitative analysis
We find a sphere at z = −70 μm shows smear ghost with high-frequency grids and blocks even at z = +50 μm after Light field microscopy (LFM) reconstruction, which is very different from a conventional widefield microscope whose defocus pattern is smooth (Fig. S4a)
Summary
Cellular motions and activities in vivo are usually in millisecond time-scale and in 3D space, including voltage and calcium transients of neurons[1,2], blood cell flows in beating hearts[3], and membrane dynamics in embryo cells[4] Observing and understanding these fantastic phenomena requires abilities to record cellular structures with a high spatiotemporal resolution in 3D. Light field microscopy (LFM) emerges as a popular tool in incoherent imaging of volumetric biological samples within a single shot[13,14,15,16,17,18,19]. LFM has achieved great success, current LFM implementations suffer several disadvantages: (1) inherent trade-offs between improving reconstruction contrast and reducing ringing effects at edges; (2) severe block-wise artifacts near the native image plane (NIP)[13]; (3) contaminations to 3D-resolved structures from depth crosstalk; and (4) quick performance degradation under low single-to-noise ratio (SNR)
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