Abstract
A critical challenge for fluorescence imaging is the loss of high frequency components in the detection path. Such a loss can be related to the limited numerical aperture of the detection optics, aberrations of the lens, and tissue turbidity. In this paper, we report an imaging scheme that integrates multilayer sample modeling, ptychography-inspired recovery procedures, and lensless single-pixel detection to tackle this challenge. In the reported scheme, we directly placed a 3D sample on top of a single-pixel detector. We then used a known mask to generate speckle patterns in 3D and scanned this known mask to different positions for sample illumination. The sample was then modeled as multiple layers and the captured 1D fluorescence signals were used to recover multiple sample images along the z axis. The reported scheme may find applications in 3D fluorescence sectioning, time-resolved and spectrum-resolved imaging. It may also find applications in deep-tissue fluorescence imaging using the memory effect.
Highlights
A critical challenge for fluorescence imaging is the loss of high frequency components in the detection path
We directly placed a 3D sample on top of a lensless single-pixel detector; no lens is used at the detection path
Different from the previous lensless fluorescence imaging demonstrations [8, 9], the achievable resolution of the reported scheme is determined by the speckle size of the illumination patterns, where we encode the 3D sample information into 1D fluorescence measurements
Summary
A critical challenge for fluorescence imaging is the loss of high frequency components in the detection path. We report an imaging scheme that integrates three innovations to tackle this challenge: 1) multilayer sample modeling [1, 2], 2) ptychography-inspired recovery procedures [3,4,5,6], and 3) lensless single-pixel detection [7]. Different from the previous lensless fluorescence imaging demonstrations [8, 9], the achievable resolution of the reported scheme is determined by the speckle size of the illumination patterns, where we encode the 3D sample information into 1D fluorescence measurements. We combine the pattern-illumination strategy with single-pixel detection scheme for multiplexed lensless fluorescence imaging. We propose a multilayer single-pixel imaging framework for recovering 3D sample information from 1D fluorescence signals.
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