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Several image-based biomedical diagnoses require high-resolution imaging capabilities at large spatial scales. However, conventional microscopes exhibit an inherent trade-off between depth-of-field (DoF) and spatial resolution, and thus require objects to be refocused at each lateral location, which is time consuming. Here, we present a computational imaging platform, termed E2E-BPF microscope, which enables large-area, high-resolution imaging of large-scale objects without serial refocusing. This method involves a physics-incorporated, deep-learned design of binary phase filter (BPF) and jointly optimized deconvolution neural network, which altogether produces high-resolution, high-contrast images over extended depth ranges. We demonstrate the method through numerical simulations and experiments with fluorescently labeled beads, cells and tissue section, and present high-resolution imaging capability over a 15.5-fold larger DoF than the conventional microscope. Our method provides highly effective and scalable strategy for DoF-extended optical imaging system, and is expected to find numerous applications in rapid image-based diagnosis, optical vision, and metrology. The E2E-BPF microscope, a DoF-extension computational imaging platform, enabled by an end-to-end optimized binary phase filter and image reconstruction, facilitates high-resolution imaging over an extended DoF without refocusing.

Birefringence, an inherent characteristic of optically anisotropic materials, is widely utilized in various imaging applications ranging from material characterizations to clinical diagnosis. Polarized light microscopy enables high-resolution, high-contrast imaging of optically anisotropic specimens, but it is associated with mechanical rotations of polarizer/analyzer and relatively complex optical designs. Here, we present a form of lens-less polarization-sensitive microscopy capable of complex and birefringence imaging of transparent objects without an optical lens and any moving parts. Our method exploits an optical mask-modulated polarization image sensor and single-input-state LED illumination design to obtain complex and birefringence images of the object via ptychographic phase retrieval. Using a camera with a pixel size of 3.45 μm, the method achieves birefringence imaging with a half-pitch resolution of 2.46 μm over a 59.74 mm 2  field-of-view, which corresponds to a space-bandwidth product of 9.9 megapixels. We demonstrate the high-resolution, large-area, phase and birefringence imaging capability of our method by presenting the phase and birefringence images of various anisotropic objects, including a monosodium urate crystal, and excised mouse eye and heart tissues.

Gross total resection (GTR) of glioma is critical for improving the survival rate of glioma patients. One of the greatest challenges for achieving GTR is the difficulty in discriminating low grade tumor or peritumor regions that have an intact blood brain barrier (BBB) from normal brain tissues and delineating glioma margins during surgery. Here we present a highly sensitive, label-free terahertz reflectometry imaging (TRI) that overcomes current key limitations for intraoperative detection of World Health Organization (WHO) grade II (low grade), and grade III and IV (high grade) gliomas. We demonstrate that TRI provides tumor discrimination and delineation of tumor margins in brain tissues with high sensitivity on the basis of Hematoxylin and eosin (H&E) stained image. TRI may help neurosurgeons to remove gliomas completely by providing visualization of tumor margins in WHO grade II, III, and IV gliomas without contrast agents, and hence, improve patient outcomes.

Optical anisotropy, which is an intrinsic property of many materials, originates from the structural arrangement of molecular structures, and to date, various polarization-sensitive imaging (PSI) methods have been developed to investigate the nature of anisotropic materials. In particular, the recently developed tomographic PSI technologies enable the investigation of anisotropic materials through volumetric mappings of the anisotropy distribution of these materials. However, these reported methods mostly operate on a single scattering model, and are thus not suitable for three-dimensional (3D) PSI imaging of multiple scattering samples. Here, we present a novel reference-free 3D polarization-sensitive computational imaging technique—polarization-sensitive intensity diffraction tomography (PS-IDT)—that enables the reconstruction of 3D anisotropy distribution of both weakly and multiple scattering specimens from multiple intensity-only measurements. A 3D anisotropic object is illuminated by circularly polarized plane waves at various illumination angles to encode the isotropic and anisotropic structural information into 2D intensity information. These information are then recorded separately through two orthogonal analyzer states, and a 3D Jones matrix is iteratively reconstructed based on the vectorial multi-slice beam propagation model and gradient descent method. We demonstrate the 3D anisotropy imaging capabilities of PS-IDT by presenting 3D anisotropy maps of various samples, including potato starch granules and tardigrade. The three-dimensional (3D) distribution of isotropic and anisotropic properties of multi-scattering objects can be effectively encoded into multiple intensity images at different input polarization states and illumination angles. Polarization-sensitive intensity diffraction tomography (PS-IDT) has demonstrated the tomographic reconstruction of 3D multiple scattering objects with fully or partially distributed anisotropy structures using vectorial multi-slice beam propagation forward model and optimization approach from captured phaseless measurements.

We present a portable multi-contrast microscope capable of producing bright-field, dark-field, and differential phase contrast images of thin biological specimens on a smartphone platform. The microscopy method is based on an imaging scheme termed “color-coded light-emitting-diode (LED) microscopy (cLEDscope),” in which a specimen is illuminated with a color-coded LED array and light transmitted through the specimen is recorded by a color image sensor. Decomposition of the image into red, green, and blue colors and subsequent computation enable multi-contrast imaging in a single shot. In order to transform a smartphone into a multi-contrast imaging device, we developed an add-on module composed of a patterned color micro-LED array, specimen stage, and miniature objective. Simple installation of this module onto a smartphone enables multi-contrast imaging of transparent specimens. In addition, an Android-based app was implemented to acquire an image, perform the associated computation, and display the multi-contrast images in real time. Herein, the details of our smartphone module and experimental demonstrations with various biological specimens are presented.

Conventional methods for analyzing heavy metal contamination in soil and water generally require laboratory equipped instruments, complex procedures, skilled personnel and a significant amount of time. With the advancement in computing and multitasking performances, smartphone-based sensors potentially allow the transition of the laboratory-based analytical processes to field applicable, simple methods. In the present work, we demonstrate the novel miniaturized setup for simultaneous sample preparation and smartphone-based optical sensing of arsenic As(III) in the contaminated soil. Colorimetric detection protocol utilizing aptamers, gold nanoparticles and NaCl have been optimized and tested on the PDMS-chip to obtain the high sensitivity with the limit of detection of 0.71 ppm (in the sample) and a correlation coefficient of 0.98. The performance of the device is further demonstrated through the comparative analysis of arsenic-spiked soil samples with standard laboratory method, and a good agreement with a correlation coefficient of 0.9917 and the average difference of 0.37 ppm, are experimentally achieved. With the android application on the device to run the experiment, the whole process from sample preparation to detection is completed within 3 hours without the necessity of skilled personnel. The approximate cost of setup is estimated around 1 USD, weight 55 g. Therefore, the presented method offers the simple, rapid, portable and cost-effective means for onsite sensing of arsenic in soil. Combined with the geometric information inside the smartphones, the system will allow the monitoring of the contamination status of soils in a nation-wide manner.

Diabetes affects the structure of the blood vessel walls. Since the blood vessel walls are made of birefringent organized tissue, any change or damage to this organization can be evaluated using polarization-sensitive optical coherence tomography (PS-OCT). In this paper, we used PS-OCT along with the blood vessel wall birefringence index (BBI = thickness/birefringence2) to non-invasively assess the structural integrity of the human retinal blood vessel walls in patients with diabetes and compared the results to those of healthy subjects. PS-OCT measurements revealed that blood vessel walls of diabetic patients exhibit a much higher birefringence while having the same wall thickness and therefore lower BBI values. Applying BBI to diagnose diabetes demonstrated high accuracy (93%), sensitivity (93%) and specificity (93%). PS-OCT measurements can quantify small changes in the polarization properties of retinal vessel walls associated with diabetes, which provides researchers with a new imaging tool to determine the effects of exercise, medication, and alternative diets on the development of diabetes.

In tissue engineering, microstructure and material composition of tissue scaffolds have major influences on the proliferation and differentiation of cells in the scaffolds. However, once tissue scaffolds implanted, it is extremely difficult to monitor the change of their microstructure and compositions during tissue regeneration. Here, we report how random lasing can be utilized to non-invasively monitor the structure and composition of scaffolds. We hypothesize that morphological and compositional change of silk fibroin (SF) scaffolds can be conveniently detected based on random lasing responses. Engineered SF scaffolds with hydroxyapatite (HAP) nanoparticles and controlled pore alignment were fabricated, and their random lasing responses were analyzed depending on the concentration of HAP nanoparticles and the degree of internal pore alignment. We also examined the real-time random lasing responses of porous SF scaffolds by applying a compressive force to the scaffolds. Introduction of HAP nanoparticles lowered the lasing thresholds and narrowed the random lasing (RL) width dramatically, which is likely due to the increase in heterogeneity in both refractive index and physical arrangement within the SF and HAP composites. The strong dependency of RL response on pore alignment was also measured and validated by numerical calculation with the finite element method (FEM). Finally, real-time monitoring of RL on compressed scaffolds demonstrated the possibility of using RL as a monitoring tool for structural change of SF scaffolds in vivo .

Owing to the tremendous demands for high-resolution pixel-scale thin lenses in displays, we developed a graphene-based ultrathin square subpixel lens (USSL) capable of electrically tuneable focusing (ETF) with a performance competitive with that of a typical mechanical refractive lens. The fringe field due to a voltage bias in the graphene proves that our ETF-USSL can focus light onto a single point regardless of the wavelength of the visible light—by controlling the carriers at the Dirac point using radially patterned graphene layers, the focal length of the planar structure can be adjusted without changing the curvature or position of the lens. A high focusing efficiency of over 60% at a visible wavelength of 405 nm was achieved with a lens thickness of <13 nm, and a change of 19.42% in the focal length with a 9% increase in transmission was exhibited under a driving voltage. This design is first presented as an ETF-USSL that can be controlled in pixel units of flat panel displays for visible light. It can be easily applied as an add-on to high resolution, slim displays and provides a new direction for the application of multifunctional autostereoscopic displays.Graphene: ultrathin tuneable lensGraphene-based ultrathin lenses with an electrically tuneable focal length could prove useful for providing displays with autostereoscopic 3D functionality, multiview or privacy protection. Developed by scientists in South Korea, the UK and the US, the lenses are just 13 nm thick and are based on a Fresnel Zone Plate (FZP) design made from a series of concentric rings of graphene on a glass substrate. Consisting of up to 5 layers of graphene that is patterned by focused ion-beam milling, the lenses offer a 60% transmission in the visible region and a focal length of 200–300 µm that can be tuned within ~20% range by applying a DC bias voltage. The applied voltage changes the charge carrier density in the graphene, modifying the topology of the FZP and thus its focusing behaviour.

Binary phase filters (BPFs) form a special class of optical structure characterized by their distinct concentric rings of alternating 0-π phases. Once placed in the pupil plane of a focusing lens, a BPF generates a sharp elongated focus, which can be utilized for diverse applications ranging from optical trapping to focus scanning microscopy. As demand for BPFs continues to expand, new design techniques are required to tune and optimize filter performance; in this paper, a topology optimization method is presented to extend BPF’s depth-of-focus while maintaining a sharp lateral resolution. In general, binary phase filters can be completely described by three designable characteristics: the radial location of each ring, the width of each ring, and the total number of rings. Conventional BPF design methods typically only consider two of these key design characteristics, often with a predefined number of rings and subsequent sizing optimization of radial locations and widths. Furthermore, these methods often rely on inefficient non-deterministic optimizers like particle swarm and simulated annealing. These implementations ultimately limit design freedom and often require manual investigation of multiple configurations at the expense of computational time and solution quality. Instead, this paper introduces topology optimization (TO) as the first and only method for BPF generation capable of considering all three design characteristics simultaneously and without any predefined assumptions. Here, the TO-based approach is first initialized with a series of concentric rings to cover the entire design domain. Then, similar to classical material distribution problems, the phase value of each concentric ring is optimized directly to satisfy the objective and constraint functions using gradient-based algorithms. This paper describes the new TO-based approach and demonstrates fundamental capabilities and design advantages. Numerical results are validated experimentally and compared with existing approaches with an emphasis on quantitative performance, non-intuitive structure generation, and computational efficiency.