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1. Closed-loop wavefront sensing and correction in the mouse brain with computed optical coherence microscopy

   https://doi.org/10.1364/BOE.427979  

   Liu, Siyang ; Xia, Fei ; Yang, Xusan ; Wu, Meiqi ; Bizimana, Laurie A. ; Xu, Chris ; Adie, Steven G. ( July 2021 , Biomedical Optics Express)

   Optical coherence microscopy (OCM) uses interferometric detection to capture the complex optical field with high sensitivity, which enables computational wavefront retrieval using back-scattered light from the sample. Compared to a conventional wavefront sensor, aberration sensing with OCM via computational adaptive optics (CAO) leverages coherence and confocal gating to obtain signals from the focus with less cross-talk from other depths or transverse locations within the field-of-view. Here, we present an investigation of the performance of CAO-based aberration sensing in simulation, bead phantoms, andex vivomouse brain tissue. We demonstrate that, due to the influence of the double-pass confocal OCM imaging geometry on the shape of computed pupil functions, computational sensing of high-order aberrations can suffer from signal attenuation in certain spatial-frequency bands and shape similarity with lower order counterparts. However, by sensing and correcting only low-order aberrations (astigmatism, coma, and trefoil), we still successfully corrected tissue-induced aberrations, leading to 3× increase in OCM signal intensity at a depth of ∼0.9 mm in a freshly dissectedex vivomouse brain.

    

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2. Millisecond exoplanet imaging: I. method and simulation results

   https://doi.org/10.1364/JOSAA.426046  

   Rodack, Alexander T. ; Frazin, Richard A. ; Males, Jared R. ; Guyon, Olivier ( September 2021 , Journal of the Optical Society of America A)

   One of the top priorities in observational astronomy is the direct imaging and characterization of extrasolar planets (exoplanets) and planetary systems. Direct images of rocky exoplanets are of particular interest in the search for life beyond the Earth, but they tend to be rather challenging targets since they are orders-of-magnitude dimmer than their host stars and are separated by small angular distances that are comparable to the classical$\mathrm{\lambda <\#comment/>}/D$diffraction limit, even for the coming generation of 30 m class telescopes. Current and planned efforts for ground-based direct imaging of exoplanets combine high-order adaptive optics (AO) with a stellar coronagraph observing at wavelengths ranging from the visible to the mid-IR. The primary barrier to achieving high contrast with current direct imaging methods is quasi-static speckles, caused largely by non-common path aberrations (NCPAs) in the coronagraph optical train. Recent work has demonstrated that millisecond imaging, which effectively “freezes” the atmosphere’s turbulent phase screens, should allow the wavefront sensor (WFS) telemetry to be used as a probe of the optical system to measure NCPAs. Starting with a realistic model of a telescope with an AO system and a stellar coronagraph, this paper provides simulations of several closely related regression models that take advantage of millisecond telemetry from the WFS and coronagraph’s science camera. The simplest regression model, called the naïve estimator, does not treat the noise and other sources of information loss in the WFS. Despite its flaws, in one of the simulations presented herein, the naïve estimator provides a useful estimate of an NCPA of$\sim <\#comment/>0.5$radian RMS ($\approx <\#comment/>\mathrm{\lambda <\#comment/>}/13$), with an accuracy of$\sim <\#comment/>0.06$radian RMS in 1 min of simulated sky time on a magnitude 8 star. Thebias-corrected estimatorgeneralizes the regression model to account for the noise and information loss in the WFS. A simulation of the bias-corrected estimator with 4 min of sky time included an NCPA of$\sim <\#comment/>0.05$radian RMS ($\approx <\#comment/>\mathrm{\lambda <\#comment/>}/130$) and an extended exoplanet scene. The joint regression of the bias-corrected estimator simultaneously achieved an NCPA estimate with an accuracy of$\sim <\#comment/>5\times <\#comment/>{10}^{-<\#comment/>3}$radian RMS and an estimate of the exoplanet scene that was free of the self-subtraction artifacts typically associated with differential imaging. The$5\mathrm{\sigma <\#comment/>}$contrast achieved by imaging of the exoplanet scene was$\sim <\#comment/>1.7\times <\#comment/>{10}^{-<\#comment/>4}$at a distance of$3\mathrm{\lambda <\#comment/>}/D$from the star and$\sim <\#comment/>2.1\times <\#comment/>{10}^{-<\#comment/>5}$at$10\mathrm{\lambda <\#comment/>}/D$. These contrast values are comparable to the very best on-sky results obtained from multi-wavelength observations that employ both angular differential imaging (ADI) and spectral differential imaging (SDI). This comparable performance is despite the fact that our simulations are quasi-monochromatic, which makes SDI impossible, nor do they have diurnal field rotation, which makes ADI impossible. The error covariance matrix of the joint regression shows substantial correlations in the exoplanet and NCPA estimation errors, indicating that exoplanet intensity and NCPA need to be estimated self-consistently to achieve high contrast.

    

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3. Millisecond exoplanet imaging: II. regression equations and technical discussion

   https://doi.org/10.1364/JOSAA.426339  

   Frazin, Richard A. ; Rodack, Alexander T. ( September 2021 , Journal of the Optical Society of America A)

   The leading difficulty in achieving the contrast necessary to directly image exoplanets and associated structures (e.g., protoplanetary disks) at wavelengths ranging from the visible to the infrared is quasi-static speckles (QSSs). QSSs are hard to distinguish from planets at the necessary level of precision to achieve high contrast. QSSs are the result of hardware aberrations that are not compensated for by the adaptive optics (AO) system; these aberrations are called non-common path aberrations (NCPAs). In 2013, Frazin showed how simultaneous millisecond telemetry from the wavefront sensor (WFS) and a science camera behind a stellar coronagraph can be used as input into a regression scheme that simultaneously and self-consistently estimates NCPAs and the sought-after image of the planetary system (exoplanetimage). When run in a closed-loop configuration, the WFS measures the corrected wavefront, called theAO residual(AOR)wavefront. The physical principle underlying the regression method is rather simple: when an image is formed at the science camera, the AOR modules both the speckles arising from NCPAs as well as the planetary image. Therefore, the AOR can be used as a probe to estimate NCPA and the exoplanet image via regression techniques. The regression approach is made more difficult by the fact that the AOR is not exactly known since it can be estimated only from the WFS telemetry. The simulations in the Part I paper provide results on the joint regression on NCPAs and the exoplanet image from three different methods, calledideal,naïve, andbias-correctedestimators. The ideal estimator is not physically realizable (it is useful as a benchmark for simulation studies), but the other two are. The ideal estimator uses true AOR values (available in simulation studies), but it treats the noise in focal plane images via standard linearized regression. Naïve regression uses the same regression equations as the ideal estimator, except that it substitutes the estimated values of the AOR for true AOR values in the regression formulas, which can result in problematic biases (however, Part I provides an example in which the naïve estimate makes a useful estimate of NCPAs). The bias-corrected estimator treats the errors in AOR estimates, but it requires the probability distribution that governs the errors in AOR estimates. This paper provides the regression equations for ideal, naïve, and bias-corrected estimators, as well as a supporting technical discussion.

    

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4. Sparse decomposition light-field microscopy for high speed imaging of neuronal activity

   https://doi.org/10.1364/OPTICA.392805  

   Yoon, Young-Gyu ; Wang, Zeguan ; Pak, Nikita ; Park, Demian ; Dai, Peilun ; Kang, Jeong Seuk ; Suk, Ho-Jun ; Symvoulidis, Panagiotis ; Guner-Ataman, Burcu ; Wang, Kai ; et al ( October 2020 , Optica)

   One of the major challenges in large scale optical imaging of neuronal activity is to simultaneously achieve sufficient temporal and spatial resolution across a large volume. Here, we introduce sparse decomposition light-field microscopy (SDLFM), a computational imaging technique based on light-field microscopy (LFM) that takes algorithmic advantage of the high temporal resolution of LFM and the inherent temporal sparsity of spikes to improve effective spatial resolution and signal-to-noise ratios (SNRs). With increased effective spatial resolution and SNRs, neuronal activity at the single-cell level can be recovered over a large volume. We demonstrate the single-cell imaging capability of SDLFM within vivoimaging of neuronal activity of whole brains of larval zebrafish with estimated lateral and axial resolutions of$\sim <\#comment/>3.5\text{µ<\#comment/>}\mathrm{m}$and$\sim <\#comment/>7.4\text{µ<\#comment/>}\mathrm{m}$, respectively, acquired at volumetric imaging rates up to 50 Hz. We also show that SDLFM increases the quality of neural imaging in adult fruit flies.

    

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5. Computational 3D microscopy with optical coherence refraction tomography

   https://doi.org/10.1364/OPTICA.454860  

   Zhou, Kevin C. ; McNabb, Ryan P. ; Qian, Ruobing ; Degan, Simone ; Dhalla, Al-Hafeez ; Farsiu, Sina ; Izatt, Joseph A. ( June 2022 , Optica)

   Optical coherence tomography (OCT) has seen widespread success as anin vivoclinical diagnostic 3D imaging modality, impacting areas including ophthalmology, cardiology, and gastroenterology. Despite its many advantages, such as high sensitivity, speed, and depth penetration, OCT suffers from several shortcomings that ultimately limit its utility as a 3D microscopy tool, such as its pervasive coherent speckle noise and poor lateral resolution required to maintain millimeter-scale imaging depths. Here, we present 3D optical coherence refraction tomography (OCRT), a computational extension of OCT that synthesizes an incoherent contrast mechanism by combining multiple OCT volumes, acquired across two rotation axes, to form a resolution-enhanced, speckle-reduced, refraction-corrected 3D reconstruction. Our label-free computational 3D microscope features a novel optical design incorporating a parabolic mirror to enable the capture of 5D plenoptic datasets, consisting of millimetric 3D fields of view over up to$\pm <\#comment/>{75}^{\circ <\#comment/>}$without moving the sample. We demonstrate that 3D OCRT reveals 3D features unobserved by conventional OCT in fruit fly, zebrafish, and mouse samples.

    

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