In light-field microscopy, a single point emitter gives rise to a complex diffraction pattern, which varies with the position of the emitter in object space. In order to use deconvolution-based wave-optical reconstruction schemes for light-field imaging systems, established methods rely on theoretical estimation of such diffraction patterns. In this paper we propose a novel method for direct experimental estimation of the light-field point spread function. Our approach relies on a modified reversed micro-Hartmann test to acquire a composite light-field point spread function of several thousand point emitters in the object plane simultaneously. By using fiducial markers and a custom image processing algorithm we separate the contributions of individual point emitters directly in raw light-field images and allow the construction of the forward imaging process without any prior assumption about the optical system required. The constructed forward imaging model can finally be applied in the 3D-deconvolution based wave-optical reconstruction scheme.
In addition to the two-dimensional intensity distribution in the image plane, light field microscopes capture information about the angle of the incident radiation. This information can be used to extract depth information about the object, calculate all-in-focus images and perform three-dimensional reconstructions from a single exposure. In combination with automated microscopy setups, this makes the technique a promising tool for high-throughput, three-dimensional cell assay evaluation which could substantially improve drug development and screening. To this end, we have developed a novel generalized calibration and three-dimensional reconstruction scheme for a lightfield fluorescence microscope setup. The scheme can handle Keplerian and Galilean light field camera configurations added to infinity corrected microscopes configured to be telecentric as well as non-telecentric or hypercentric. The latter provides a significant advantage over the state of the art as it allows for an application specific optimization of lateral and axial resolution, field-of-view, and depth-of-focus. The reconstruction itself is performed iteratively using an expectation maximization algorithm. Super-resolved reconstructions can be achieved by including experimentally measured pointspread- functions. To reduce the required computational power, sparsity and periodicity of the system matrix relating object space to light field space is exploited. This is particularly challenging for the non-telecentric cases, where the voxel size of the reconstructed object space depends on the axial coordinate. We provide details on the experimental setup and the reconstruction algorithm, and present results on the experimental verification of theoretical performance parameters as well as successful reconstructions of fluorescent beads and three-dimensional cell spheroids.
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