Fourier transform digital holographic adaptive optics imaging system

Quantitative differential phase contrast (DPC) microscopy with computational aberration correction

Differential Phase Contrast (DPC) microscopy is a practical method for recovering quantitative phase from intensity images captured with different source patterns in an LED array microscope. Being a partially coherent imaging method, DPC does not suffer from speckle artifacts and achieves 2× better resolution than coherent methods. Like all imaging systems, however, DPC is susceptible to aberrations. Here, we propose a method of algorithmic self-calibration for DPC where we simultaneously recover the complex-field of the sample and the spatially-variant aberrations of the system, using 4 images with different illumination source patterns. The resulting phase reconstructions are digitally aberration-corrected.

Digital adaptive optics confocal microscopy based on iterative retrieval of optical aberration from a guidestar hologram

Guidestar hologram based digital adaptive optics (DAO) is one recently emerging active imaging modality. It records each complex distorted line field reflected or scattered from the sample by an off-axis digital hologram, measures the optical aberration from a separate off-axis digital guidestar hologram, and removes the optical aberration from the distorted line fields by numerical processing. In previously demonstrated DAO systems, the optical aberration was directly retrieved from the guidestar hologram by taking its Fourier transform and extracting the phase term. For the direct retrieval method (DRM), when the sample is not coincident with the guidestar focal plane, the accuracy of the optical aberration retrieved by DRM undergoes a fast decay, leading to quality deterioration of corrected images. To tackle this problem, we explore here an image metrics-based iterative method (MIM) to retrieve the optical aberration from the guidestar hologram. Using an aberrated objective lens and scattering samples, we demonstrate that MIM can improve the accuracy of the retrieved aberrations from both focused and defocused guidestar holograms, compared to DRM, to improve the robustness of the DAO.

Digital adaptive optics line-scanning confocal imaging system

A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

Quantitative phase-contrast confocal microscope

We present a quantitative phase-contrast confocal microscope (QPCCM) by combining a line-scanning confocal system with digital holography (DH). This combination can merge the merits of these two different imaging modalities. High-contrast intensity images with low coherent noise, and the optical sectioning capability are made available due to the confocality. Phase profiles of the samples become accessible thanks to DH. QPCCM is able to quantitatively measure the phase variations of optical sections of the opaque samples and has the potential to take high-quality intensity and phase images of non-opaque samples such as many biological samples. Because each line scan is recorded by a hologram that may contain the optical aberrations of the system, it opens avenues for a variety of numerical aberration compensation methods and development of full digital adaptive optics confocal system to emulate current hardware-based adaptive optics system for biomedical imaging, especially ophthalmic imaging. Preliminary experiments with a microscope objective of NA 0.65 and 40 × on opaque samples are presented to demonstrate this idea. The measured lateral and axial resolutions of the intensity images from the current system are ~0.64μm and ~2.70μm respectively. The noise level of the phase profile by QPCCM is ~2.4nm which is better than the result by DH.

Phase aberration correction by correlation in digital holographic adaptive optics

We present a phase aberration correction method based on the correlation between the complex full-field and guide-star holograms in the context of digital holographic adaptive optics (DHAO). Removal of a global quadratic phase term before the correlation operation plays an important role in the correction. Correlation operation can remove the phase aberration at the entrance pupil plane and automatically refocus the corrected optical field. Except for the assumption that most aberrations lie at or close to the entrance pupil, the presented method does not impose any other constraints on the optical systems. Thus, it greatly enhances the flexibility of the optical design for DHAO systems in vision science and microscopy. Theoretical studies show that the previously proposed Fourier transform DHAO (FTDHAO) is just a special case of this general correction method, where the global quadratic phase term and a defocus term disappear. Hence, this correction method realizes the generalization of FTDHAO into arbitrary DHAO systems. The effectiveness and robustness of this method are demonstrated by simulations and experiments.