Sex differences in zymosan-induced behavioral visceral hypersensitivity and colorectal afferent sensitization.

Sex differences in visceral nociception have been reported in clinical and preclinical studies, but the potential differences in sensory neural encoding of the colorectum between males and females are not well understood. In this study, we systematically assessed sex differences in colorectal neural encoding by conducting high-throughput optical recordings in intact dorsal root ganglia (DRGs) from control and visceral hypersensitive mice. We found an apparent sex difference in zymosan-induced behavioral visceral hypersensitivity: enhanced visceromotor responses to colorectal distension were observed only in male mice, not in female mice. In addition, a higher number of mechanosensitive colorectal afferents were identified per mouse in the zymosan-treated male group than in the saline-treated male group, whereas the mechanosensitive afferents identified per mouse were comparable between the zymosan- and saline-treated female groups. The increased number of identified afferents in zymosan-treated male mice was predominantly from thoracolumbar (TL) innervation, which agrees with the significant increase in the TL afferent proportion in the zymosan group as compared with the control group in male mice. In contrast, female mice showed no difference in the proportion of colorectal neurons between saline- and zymosan-treated groups. Our results revealed a significant sex difference in colorectal afferent innervation and sensitization in the context of behavioral visceral hypersensitivity, which could drive differential clinical symptoms in male and female patients.NEW & NOTEWORTHY We used high-throughput GCaMP6f recordings to study 2,275 mechanosensitive colorectal afferents in mice. Our results revealed significant sex differences in the zymosan-induced behavioral visceral hypersensitivity, which were present in male but not female mice. Male mice also showed sensitization of colorectal afferents in the thoracolumbar pathway, whereas female mice did not. These findings highlight sex differences in sensory neural anatomy and function of the colorectum, with implications for sex-specific therapies for treating visceral pain.

Fly-scan high-throughput coded ptychographic microscopy via active micro-vibration and rolling-shutter distortion correction.

Recent advancements in ptychography have demonstrated the potential of coded ptychography (CP) for high-resolution optical imaging in a lensless configuration. However, CP suffers imaging throughput limitations due to scanning inefficiencies. To address this, we propose what we believe is a novel 'fly-scan' scanning strategy utilizing two eccentric rotating mass (ERM) vibration motors for high-throughput coded ptychographic microscopy. The intrinsic continuity of the 'fly-scan' technique effectively eliminates the scanning overhead typically encountered during data acquisition. Additionally, its randomized scanning trajectory considerably reduces periodic artifacts in image reconstruction. We also developed what we believe to be a novel rolling-shutter distortion correction algorithm to fix the rolling-shutter effects. We built up a low-cost, DIY-made prototype platform and validated our approach with various samples including a resolution target, a quantitative phase target, a thick potato sample and biospecimens. The reported platform may offer a cost-effective and turnkey solution for high-throughput bio-imaging.

Full-resolution, full-field-of-view, and high-quality fast Fourier single-pixel imaging.

Fourier single-pixel imaging (FSI) uses Fourier basis patterns for spatial light modulation to acquire the Fourier spectrum of the object image. The object image can be reconstructed via an inverse Fourier transform. However, the Fourier basis patterns are inherently gray scale, which results in the difficulty that the patterns can hardly be generated at a high speed by using a commonly used spatial light modulator-digital micromirrors device. To tackle this problem, fast FSI, which uses upsampled and dithered Fourier basis patterns to approximate the gray scale patterns, has been reported, but the achievable spatial resolution has to be sacrificed in the pattern upsampling process. Here we propose a method that can achieve not only full-resolution but also full-field-of-view and high-quality FSI. The key to the proposed method is to use a new, to the best of our knowledge, error diffusion dithering algorithm combined with two different scanning strategies to generate two sets of binarized Fourier basis patterns for spatial light modulation. As a result, two images with a sub-pixel shift from each other are reconstructed. It results in the final high-quality reconstruction by synthesizing the two images. We experimentally demonstrate the method can produce a high-quality 1024 × 768-pixel and full resolution image with a digital micromirror device with 1024 × 768 micromirrors.

Remote referencing strategy for high-resolution coded ptychographic imaging.

The applications of conventional ptychography are limited by its relatively low resolution and throughput in the visible light regime. The new development of coded ptychography (CP) has addressed these issues and achieved the highest numerical aperture for large-area optical imaging in a lensless configuration. A high-quality reconstruction of CP relies on precise tracking of the coded sensor's positional shifts. The coded layer on the sensor, however, prevents the use of cross correlation analysis for motion tracking. Here we derive and analyze the motion tracking model of CP. A novel, to the best of our knowledge, remote referencing scheme and its subsequent refinement pipeline are developed for blind image acquisition. By using this approach, we can suppress the correlation peak caused by the coded surface and recover the positional shifts with deep sub-pixel accuracy. In contrast with common positional refinement methods, the reported approach can be disentangled from the iterative phase retrieval process and is computationally efficient. It allows blind image acquisition without motion feedback from the scanning process. It also provides a robust and reliable solution for implementing ptychography with high imaging throughput. We validate this approach by performing high-resolution whole slide imaging of bio-specimens.

Image-free active autofocusing with dual modulation and its application to Fourier single-pixel imaging.

Autofocusing is widely used in applications where sharp image acquisition or projection is needed. Here we report an active autofocusing method for sharp image projection. The method works with wide-field structured illumination and single-pixel detection. To find the focus position, the method illuminates the target object with a set of 3-step phase-shifting Fourier basis patterns repeatedly and collects the backscattered light by using a single-pixel detector through a grating. Dual modulation-dynamic modulation by the time-varying structured illumination and static modulation by the grating-embeds the depth information for the target object in the resulting single-pixel measurements. As such, the focus position can be determined by recovering the Fourier coefficients from the single-pixel measurements and searching for the coefficient with the maximum magnitude. High-speed spatial light modulation not only enables rapid autofocusing but also makes the method work even when the lens system is in continuous motion or the focal length of the lens is continuously adjusted. We experimentally validate the reported method in a self-built digital projector and demonstrate the application of the method in Fourier single-pixel imaging.

Batch-based alternating direction methods of multipliers for Fourier ptychography.

Fourier ptychography (FP) has been developed as a general imaging tool for various applications. However, the redundancy data has to be enforced to get a stable recovery, leading to a large dataset and a high computational cost. Based on the additive property of the optical pupils in FP recovery, we report batch-based alternating direction methods of multipliers (ADMM) for FP reconstruction. The reported scheme is performed by implementing partial updates in sub-problems of the standard ADMM. We validate the reconstruction performance using both simulated and experimental measurements. Compared with the embedded pupil function recovery (EPRY) algorithm, the proposed algorithms can converge faster and produce higher-quality images.

Deep distributed optimization for blind diffuser-modulation ptychography.

Blind diffuser-modulation ptychography has emerged as a low-cost technique for micro-nano holographic imaging, which enables breaking the resolution limit of optical systems. However, the existing reconstruction method requires thousands of measurements to recover object and diffuser profile simultaneously, which makes the data acquisition time-consuming and cumbersome. In this Letter, we report a novel, to the best of our knowledge, blind ptychography technique with deep distributed optimization, termed BPD2O. It decomposes the complicated optimization task into subproblems, then introduces extended ptychographical iterative engine and enhanced network solver to optimize each in a distributed strategy. In this way, BPD2O combines the advantages of both model-driven and data-driven strategies, realizing high-fidelity robust ptychography imaging. Extensive experiments validate that BPD2O can realize better resolution and lead to a reduction of more than one order of magnitude in the number of measurements.

Ringing-free fast Fourier single-pixel imaging.

Fourier single-pixel imaging (FSI) allows an image to be reconstructed by acquiring the Fourier spectrum of the image using a single-pixel detector. Fast FSI is typically achieved by acquiring a truncated Fourier spectrum, that is, only low-frequency Fourier coefficients are acquired, with the high-frequency coefficients discarded. However, the truncation of the Fourier spectrum leads to undesirable ringing artifacts in the resulting image. Ringing artifacts produce false edges in the image and reduce the image contrast, resulting in image quality degeneration. The artifact is particularly severe in dynamic FSI, where the sampling ratio is generally ultra-low. We propose an effective and fast deringing algorithm to achieve ringing-free fast FSI. The algorithm eliminates ringing artifacts through 2D sub-pixel shifting and preserves image details through image fusion. Both static and dynamic imaging results demonstrate that the proposed method can reconstruct ringing-free images from under-sampled data in FSI. The deringing algorithm not only provides FSI with the capability of fast high-quality single-pixel imaging but also might prove its applicability in other areas, such as Fourier-based data compression algorithms.

Robust multi-angle structured illumination lensless microscopy via illumination angle calibration.

Multi-angle structured illumination lensless (MASIL) microscopy enables high-resolution image recovery over a large field of view. Successful image recovery of MASIL microscopy, however, relies on an accurate knowledge of the multi-angle illumination. System misalignments and slight deviations from the true illumination angle may result in image artifacts in reconstruction. Here we report a MASIL microscopy system that is robust against illumination misalignment. To calibrate the illumination angles, we design and use a double-sided mask, which is a glass wafer fabricated with a ring-array pattern on the upper surface and a disk-array pattern on the lower surface. As such, the illumination angles can be decoded from the captured images by estimating the relative displacement of the two patterns. We experimentally demonstrate that this system can achieve successful image recovery without any prior knowledge of the illumination angles. The reported approach provides a simple yet robust resolution for wide-field lensless microscopy. It can solve the LED array misalignment problem and calibrate angle-varied illumination for a variety of applications.

Ptychography-based high-throughput lensless on-chip microscopy via incremental proximal algorithms.

Ptychography-based lensless on-chip microscopy enables high-throughput imaging by retrieving the missing phase information from intensity measurements. Numerous reconstruction algorithms for ptychography have been proposed, yet only a few incremental algorithms can be extended to lensless on-chip microscopy because of large-scale datasets but limited computational efficiency. In this paper, we propose the use of accelerated proximal gradient methods for blind ptychographic phase retrieval in lensless on-chip microscopy. Incremental gradient approaches are adopted in the reconstruction routine. Our algorithms divide the phase retrieval problem into sub-problems involving the evaluation of proximal operator, stochastic gradient descent, and Wirtinger derivatives. We benchmark the performances of accelerated proximal gradient, extended ptychographic iterative engine, and alternating direction method of multipliers, and discuss their convergence and accuracy in both noisy and noiseless cases. We also validate our algorithms using experimental datasets, where full field of view measurements are captured to recover the high-resolution complex samples. Among these algorithms, accelerated proximal gradient presents the overall best performance regarding accuracy and convergence rate. The proposed methods may find applications in ptychographic reconstruction, especially for cases where a wide field of view and high resolution are desired at the same time.

Mask-modulated lensless imaging via translated structured illumination.

Lensless microscopy technique enables high-resolution image recovery over a large field of view. By integrating the concept of phase retrieval, it can also retrieve the lost phase information from intensity-only measurements. Here we report a mask-modulated lensless imaging platform based on translated structured illumination. In the reported platform, we sandwich the object in-between a coded mask and a naked image sensor for lensless data acquisition. An LED array is used to provide angle-varied illumination for projecting a translated structured pattern without involving mechanical scanning. For different LED elements, we acquire the lensless intensity data for recovering the complex-valued object. In the reconstruction process, we employ the regularized ptychographic iterative engine and implement an up-sampling process in the reciprocal space. As demonstrated by experimental results, the reported platform is able to recover complex-valued object images with higher resolution and better quality than previous implementations. Our approach may provide a cost-effective solution for high-resolution and wide field-of-view ptychographic imaging without involving mechanical scanning.

Deep learning-enabled whole slide imaging (DeepWSI): oil-immersion quality using dry objectives, longer depth of field, higher system throughput, and better functionality.

Whole slide imaging (WSI) has moved the traditional manual slide inspection process to the era of digital pathology. A typical WSI system translates the sample to different positions and captures images using a high numerical aperture (NA) objective lens. Performing oil-immersion microscopy is a major obstacle for WSI as it requires careful liquid handling during the scanning process. Switching between dry objective and oil-immersion lens is often impossible as it disrupts the acquisition process. For a high-NA objective lens, the sub-micron depth of field also poses a challenge to acquiring in-focus images of samples with uneven topography. Additionally, it implies a small field of view for each tile, thus limiting the system throughput and resulting in a long acquisition time. Here we report a deep learning-enabled WSI platform, termed DeepWSI, to substantially improve the system performance and imaging throughput. With this platform, we show that images captured with a regular dry objective lens can be transformed into images comparable to that of a 1.4-NA oil immersion lens. Blurred images with defocus distance from -5 µm to +5 µm can be virtually refocused to the in-focus plane post measurement. We demonstrate an equivalent data throughput of >2 gigapixels per second, the highest among existing WSI systems. Using the same deep neural network, we also report a high-resolution virtual staining strategy and demonstrate it for Fourier ptychographic WSI. The DeepWSI platform may provide a turnkey solution for developing high-performance diagnostic tools for digital pathology.

High-throughput lensless whole slide imaging via continuous height-varying modulation of a tilted sensor.

We report a new, to the best of our knowledge, lensless microscopy configuration by integrating the concepts of transverse translational ptychography and defocus multi-height phase retrieval. In this approach, we place a tilted image sensor under the specimen for introducing linearly increasing phase modulation along one lateral direction. Similar to the operation of ptychography, we laterally translate the specimen and acquire the diffraction images for reconstruction. Since the axial distance between the specimen and the sensor varies at different lateral positions, laterally translating the specimen effectively introduces defocus multi-height measurements while eliminating axial scanning. Lateral translation further introduces sub-pixel shift for pixel super-resolution imaging and naturally expands the field of view for rapid whole slide imaging. We show that the equivalent height variation can be precisely estimated from the lateral shift of the specimen, thereby addressing the challenge of precise axial positioning in conventional multi-height phase retrieval. Using a sensor with 1.67 µm pixel size, our low-cost and field-portable prototype can resolve the 690 nm linewidth on the resolution target. We show that a whole slide image of a blood smear with a 120mm2 field of view can be acquired in 18 s. We also demonstrate accurate automatic white blood cell counting from the recovered image. The reported approach may provide a turnkey solution for addressing point-of-care and telemedicine-related challenges.

Single-pixel ptychography.

Ptychography is a predominant non-interferometric technique to image large complex fields but with quite a narrow working spectrum, because diffraction measurements require dense array detection with an ultra-high dynamic range. Here we report a single-pixel ptychography technique that realizes non-interferometric and non-scanning complex-field imaging in a wide waveband, where 2D dense detector arrays are not available. A single-pixel detector is placed in the far field to record the DC-only component of the diffracted wavefront scattered from the target field, which is illuminated by a sequence of binary modulation patterns. This decreases the measurements' dynamic range by several orders of magnitude. We employ an efficient single-pixel phase-retrieval algorithm to jointly recover the field's 2D amplitude and phase maps from the 1D intensity-only measurement sequence. No a priori object information is needed in the recovery process. We validate the technique's quantitative phase imaging nature using both calibrated phase objects and biological samples and demonstrate its wide working spectrum with both 488-nm visible light and 980-nm near-infrared light.

Image-free classification of fast-moving objects using "learned" structured illumination and single-pixel detection.

Object classification generally relies on image acquisition and subsequent analysis. Real-time classification of fast-moving objects is a challenging task. Here we propose an approach for real-time classification of fast-moving objects without image acquisition. The key to the approach is to use structured illumination and single-pixel detection to acquire the object features directly. A convolutional neural network (CNN) is trained to learn the object features. The "learned" object features are then used as structured patterns for structured illumination. Object classification can be achieved by picking up the resulting light signals by a single-pixel detector and feeding the single-pixel measurements to the trained CNN. In our experiments, we show that accurate and real-time classification of fast-moving objects can be achieved. Potential applications of the proposed approach include rapid classification of flowing cells, assembly-line inspection, and aircraft classification in defense applications. Benefiting from the use of a single-pixel detector, the approach might be applicable for hidden moving object classification.

Virtual brightfield and fluorescence staining for Fourier ptychography via unsupervised deep learning.

Fourier ptychographic microscopy (FPM) is a computational approach geared towards creating high-resolution and large field-of-view images without mechanical scanning. Acquiring color images of histology slides often requires sequential acquisitions with red, green, and blue illuminations. The color reconstructions often suffer from coherent artifacts that are not presented in regular incoherent microscopy images. As a result, it remains a challenge to employ FPM for digital pathology applications, where resolution and color accuracy are of critical importance. Here we report a deep learning approach for performing unsupervised image-to-image translation of FPM reconstructions. A cycle-consistent adversarial network with multiscale structure similarity loss is trained to perform virtual brightfield and fluorescence staining of the recovered FPM images. In the training stage, we feed the network with two sets of unpaired images: (1) monochromatic FPM recovery and (2) color or fluorescence images captured using a regular microscope. In the inference stage, the network takes the FPM input and outputs a virtually stained image with reduced coherent artifacts and improved image quality. We test the approach on various samples with different staining protocols. High-quality color and fluorescence reconstructions validate its effectiveness.

Super-resolved multispectral lensless microscopy via angle-tilted, wavelength-multiplexed ptychographic modulation.

We report an angle-tilted, wavelength-multiplexed ptychographic modulation approach for multispectral lensless on-chip microscopy. In this approach, we illuminate the specimen with lights at five wavelengths simultaneously. A prism is added at the illumination path for spectral dispersion. Thus, lightwaves at different wavelengths hit the specimen at slightly different incident angles, breaking the ambiguities in mixed-state ptychographic reconstruction. At the detection path, we place a thin diffuser between the specimen and the monochromatic image sensor for encoding the spectral information into 2D intensity measurements. By scanning the sample to different x-y positions, we acquire a sequence of monochromatic images for reconstructing the five complex object profiles at the five wavelengths. An up-sampling procedure is integrated into the recovery process to bypass the resolution limit imposed by the imager pixel size. We demonstrate a half-pitch resolution of 0.55 µm using an image sensor with 1.85 µm pixel size. We also demonstrate quantitative and high-quality multispectral reconstructions of stained tissue sections for digital pathology applications.

Near-field Fourier ptychography: super-resolution phase retrieval via speckle illumination.

High spatial resolution is the goal of many imaging systems. While designing a high-resolution lens with diffraction-limited performance over a large field of view remains a difficult task, creating a complex speckle pattern with wavelength-limited spatial features is easily accomplished with a simple random diffuser. With this observation and the concept of near-field ptychography, we report a new imaging modality, termed near-field Fourier ptychography, to address high-resolution imaging challenges in both microscopic and macroscopic imaging settings. 'Near-field' refers to placing the object at a short defocus distance with a large Fresnel number. We project a speckle pattern with fine spatial features on the object instead of directly resolving the spatial features via a high-resolution lens. We then translate the object (or speckle) to different positions and acquire the corresponding images by using a low-resolution lens. A ptychographic phase retrieval process is used to recover the complex object, the unknown speckle pattern, and the coherent transfer function at the same time. In a microscopic imaging setup, we use a 0.12 numerical aperture (NA) lens to achieve an NA of 0.85 in the reconstruction process. In a macroscale photographic imaging setup, we achieve ~7-fold resolution gain by using a photographic lens. The collection optics do not determine the final achievable resolution; rather, the speckle pattern's feature size does. This is similar to our recent demonstration in fluorescence imaging settings (Guo et al., Biomed. Opt. Express, 9(1), 2018). The reported imaging modality can be employed in light, coherent X-ray, and transmission electron imaging systems to increase resolution and provide quantitative absorption and object phase contrast.

Super-resolution microscopy via ptychographic structured modulation of a diffuser.

We report a new coherent imaging technique, termed ptychographic structured modulation (PSM), for quantitative super-resolution microscopy. In this technique, we place a thin diffuser (i.e., a scattering lens) in between the sample and the objective lens to modulate the complex light waves from the object. The otherwise inaccessible high-resolution object information can thus be encoded into the captured images. We then employ a ptychographic phase retrieval process to jointly recover the exit wavefront of the complex object and the unknown diffuser profile. Unlike the illumination-based super-resolution approach, the recovered image of our approach depends upon how the complex wavefront exits the sample-not enters it. Therefore, the sample thickness becomes irrelevant during reconstruction. After recovery, we can propagate the super-resolution complex wavefront to any position along the optical axis. We validate our approach using a resolution target, a quantitative phase target, a two-layer sample, and a thick polydimethylsiloxane sample. We demonstrate a 4.5-fold resolution gain over the diffraction limit. We also show that a four-fold resolution gain can be achieved with as few as ∼30 images. The reported approach may provide a quantitative super-resolution strategy for coherent light, x-ray, and electron imaging.

Axially shifted pattern illumination for macroscale turbidity suppression and virtual volumetric confocal imaging without axial scanning.

Structured illumination has been widely used for optical sectioning and 3D surface recovery. In a typical implementation, multiple images under non-uniform pattern illumination are used to recover a single object section. Axial scanning of the sample or the objective lens is needed for acquiring the 3D volumetric data. Here we demonstrate the use of axially shifted pattern illumination for virtual volumetric confocal imaging without axial scanning. In the reported approach, we project illumination patterns at a tilted angle with respect to the detection optics. As such, the illumination patterns shift laterally at different z sections, and the 3D sample information can be recovered based on the captured 2D images. We demonstrate the reported approach for virtual confocal imaging through a diffusing layer and underwater 3D imaging through diluted milk. We show that we can acquire the entire confocal volume in ∼1 s with a throughput of 420 megapixels per second. Our approach may provide new insights for developing confocal light ranging and detection systems in degraded visual environments.