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1. Needle-based deep-neural-network camera

   https://doi.org/10.1364/AO.415059  

   Guo, Ruipeng ; Nelson, Soren ; Menon, Rajesh ( March 2021 , Applied Optics)

   We experimentally demonstrate a camera whose primary optic is a cannula/needle ($\mathrm{d}\mathrm{i}\mathrm{a}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r}=0.22\mathrm{m}\mathrm{m}$and$\mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}=12.5\mathrm{m}\mathrm{m}$) that acts as a light pipe transporting light intensity from an object plane (35 cm away) to its opposite end. Deep neural networks (DNNs) are used to reconstruct color and grayscale images with a field of view of 18° and angular resolution of$\sim <\#comment/>{0.4}^{\circ <\#comment/>}$. We showed a large effective demagnification of$127\times <\#comment/>$. Most interestingly, we showed that such a camera could achieve close to diffraction-limited performance with an effective numerical aperture of 0.045, depth of focus$\sim <\#comment/>16\text{µ<\#comment/>}\mathrm{m}$, and resolution close to the sensor pixel size (3.2 µm). When trained on images with depth information, the DNN can create depth maps. Finally, we show DNN-based classification of the EMNIST dataset before and after image reconstructions. The former could be useful for imaging with enhanced privacy.

    

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2. High-speed wide-field multi-parametric photoacoustic microscopy

   https://doi.org/10.1364/OL.391824  

   Zhong, Fenghe ; Bao, Youwei ; Chen, Ruimin ; Zhou, Qifa ; Hu, Song ( May 2020 , Optics Letters)

   Capable of imaging blood perfusion, oxygenation, and flow simultaneously at the microscopic level, multi-parametric photoacoustic microscopy (PAM) has quickly emerged as a powerful tool for studying hemodynamic and metabolic changes due to physiological stimulations or pathological processes. However, the low scanning speed poised by the correlation-based blood flow measurement impedes its application in studying rapid microvascular responses. To address this challenge, we have developed a new, to the best of our knowledge, multi-parametric PAM system. By extending the optical scanning range with a cylindrically focused ultrasonic transducer (focal zone,$76\text{µ<\#comment/>}\mathrm{m}\times <\#comment/>4.5\mathrm{m}\mathrm{m}$) for simultaneous acquisition of 500 B-scans, the new system is 112 times faster than our previous multi-parametric system that uses a spherically focused transducer (focal diameter, 40 µm) and enables high-resolution imaging of blood perfusion, oxygenation, and flow over an area of$4.5\times <\#comment/>1{\mathrm{m}\mathrm{m}}^2$at a frame rate of 1 Hz. We have demonstrated the feasibility of this system in the living mouse ear. Further development of this system into reflection mode will enable real-time cortex-wide imaging of hemodynamics and metabolism in the mouse brain.

    

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3. Monolithic all-silicon flat lens for broadband LWIR imaging

   https://doi.org/10.1364/OL.426384  

   Kigner, Orrin ; Meem, Monjurul ; Baker, Brian ; Banerji, Sourangsu ; Hon, Philip W. C. ; Sensale-Rodriguez, Berardi ; Menon, Rajesh ( August 2021 , Optics Letters)

   We designed, fabricated, and characterized a flat multi-level diffractive lens comprised of only silicon with$\mathrm{d}\mathrm{i}\mathrm{a}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r}=15.2\mathrm{m}\mathrm{m}$, focal$\mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}=19\mathrm{m}\mathrm{m}$, numerical aperture of 0.371, and operating over the long-wave infrared (LWIR)$\mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{r}\mathrm{u}\mathrm{m}=8\text{µ<\#comment/>}\mathrm{m}$to 14 µm. We experimentally demonstrated a field of view of 46°, depth of focus$><\#comment/>5\mathrm{m}\mathrm{m}$, and wavelength-averaged Strehl ratio of 0.46. All of these metrics were comparable to those of a conventional refractive lens. The active device thickness is only 8 µm, and its weight (including the silicon substrate) is less than 0.2 g.

    

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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. Additive manufacturing for the development of optical/photonic systems and components

   https://doi.org/10.1364/OPTICA.451642  

   Berglund, Gregory ; Wisniowiecki, Anna ; Gawedzinski, John ; Applegate, Brian ; Tkaczyk, Tomasz S. ( June 2022 , Optica)

   The ambition of this review is to provide an up-to-date synopsis of the state of 3D printing technology for optical and photonic components, to gauge technological advances, and to discuss future opportunities. While a range of approaches have been developed and some have been commercialized, no single approach can yet simultaneously achieve small detail and low roughness at large print volumes and speed using multiple materials. Instead, each approach occupies a niche where the components/structures that can be created fit within a relatively narrow range of geometries with limited material choices. For instance, the common Fused Deposition Modeling (FDM) approach is capable of large print volumes at relatively high speeds but lacks the resolution needed for small detail ($><\#comment/>100\text{µ<\#comment/>}\mathrm{m}$) with low roughness ($><\#comment/>9\text{µ<\#comment/>}\mathrm{m}$). At the other end of the spectrum, two-photon polymerization can achieve roughness ($<<\#comment/>15\mathrm{n}\mathrm{m}$) and detail ($<<\#comment/>140\mathrm{n}\mathrm{m}$) comparable to commercial molded and polished optics. However, the practical achievable print volume and speed are orders of magnitude smaller and slower than the FDM approach. Herein, we discuss the current state-of-the-art 3D printing approaches, noting the capability of each approach and prognosticate on future innovations that could close the gaps in performance.

    

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