High-resolution quantitative phase imaging based on a spatial light modulator and incremental binary random sampling.

We propose a single-beam high-resolution quantitative phase imaging method based on a spatial light modulator (SLM) and an incremental binary random sampling (IBRS) algorithm. In this method, the image of the test object presents on the image sensor through an optical microscopy system composed of an objective lens and a collimating lens. A transmittance SLM displaying a group of well-designed IBRS patterns is inserted in the optical microscopy system to modulate the object wavefront. The phase information of the object image can be quantitatively retrieved from the recorded intensities using the IBRS algorithm and the amplitude obtained directly from the diffraction intensity. The IBRS algorithm employed in our method has higher accuracy for phase retrieval compared with our previously proposed complementary random sampling algorithm, which is confirmed by simulations. Further, we demonstrate experimentally the feasibility of our method through several examples: phase imaging of immersion oil droplets with a diffraction-limited lateral resolution of 1.54 µm and a few microbiological specimens with 0.70 µm. Experimental results reveal that our proposed method provides a feasible single-beam technique for quantitative phase imaging with a high spatial resolution.

Focus engineering based on analytical formulae for tightly focused polarized beams with arbitrary geometric configurations of linear polarization.

Highly confined electromagnetic fields with controllable intensity profiles and polarization orientations are greatly desired in many fields. In this paper, we report on the generation of highly confined fields through tightly focused locally linearly polarized beams. Using the Richards-Wolf vectorial diffraction method, we derive and build integrated analytical formulae for calculating the tightly focused field of polarized beams with arbitrary geometric configurations of linear polarization. Based on the analytical model, the focusing properties of four types of polarized light beams, i.e., linearly, azimuthally, radially, and spatially variant polarized beams, with locally linear states of polarization are investigated numerically and discussed in detail. By manipulating the radial and azimuthal indices and initial phases, we obtain a tunable three-dimensional optical cage, multifoci, optical needles, and channels in the focal volume of a high-numerical-aperture objective lens. These peculiar properties may find applications in fields such as optical trapping and manipulation of nanoparticles and super-resolution microscopy imaging.

Machine learning based on structural and FTIR spectroscopic datasets for seed autoclassification.

A single feature set is often unable to effectively classify complex biological samples due to their similar morphology and sizes. This paper proposes a protocol for the fast identification of seed medicinal materials based on micro-structural and infrared spectroscopic characteristics. Three different feature datasets, namely micro-CT, FTIR, and mixed datasets, were established via principal component analysis (PCA) and competitive adaptive reweighted sampling (CARS) and then used to train a back-propagation neural network. The mixed dataset consists of 34-dimensional micro-CT eigenvalues and 13-dimensional FTIR eigenvalues, optimized by PCA and CARS processing and then used to train a BP neural network. The results showed that the classification accuracy reached 89.5% for the micro-CT dataset and 93.3% for the FTIR dataset, and the classification accuracy of the mixed dataset achieved 99.2%, much higher than those of the traditional single feature datasets. This study provides a new protocol for multi-dimensional characteristic architecture with excellent performance for the classification and identification of Chinese medicinal materials.

Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers.

Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance.

Micro-morphological feature visualization, auto-classification, and evolution quantitative analysis of tumors by using SR-PCT.

Tissue micro-morphological abnormalities and interrelated quantitative data can provide immediate evidences for tumorigenesis and metastasis in microenvironment. However, the multiscale three-dimensional nondestructive pathological visualization, measurement, and quantitative analysis are still a challenging for the medical imaging and diagnosis. In this work, we employed the synchrotron-based X-ray phase-contrast tomography (SR-PCT) combined with phase-and-attenuation duality phase retrieval to reconstruct and extract the volumetric inner-structural characteristics of tumors in digesting system, helpful for tumor typing and statistic calculation of different tumor specimens. On the basis of the feature set including eight types of tumor micro-lesions presented by our SR-PCT reconstruction with high density resolution, the AlexNet-based deep convolutional neural network model was trained and obtained the 94.21% of average accuracy of auto-classification for the eight types of tumors in digesting system. The micro-pathomophological relationship of liver tumor angiogenesis and progression were revealed by quantitatively analyzing the microscopic changes of texture and grayscale features screened by a machine learning method of area under curve and principal component analysis. The results showed the specific path and clinical manifestations of tumor evolution and indicated that these progressions of tumor lesions rely on its inflammation microenvironment. Hence, this high phase-contrast 3D pathological characteristics and automatic analysis methods exhibited excellent recognizable and classifiable for micro tumor lesions.

All-Inorganic Perovskite CsPb2Br5 Nanosheets for Photodetector Application Based on Rapid Growth in Aqueous Phase.

All-inorganic cesium lead-halide perovskites exhibit a great development prospect in optoelectronic devices owing to their stability and remarkable optoelectronic properties. Herein, we investigate the solution-processed synthesis of perovskite CsPb2Br5 nanosheets by using aqueous and ethanol as solvents. The results show that the aqueous environment ensures the phase formation of CsPb2Br5 and that the supersaturated solution in ethanol boosts nucleation of the nanosheets. The substrate temperature is the key factor for the evolution of morphology and the variation of the thickness of CsPb2Br5 nanosheets. Lower substrate temperature (<35 °C) is conducive to the formation of evenly distributed nanosheets with less stacking. The spatial and time-resolved fluorescence spectra indicate the heterogeneity of the defect density and the recombination process in different nanosheet regions. The photodetector based on the prepared CsPb2Br5 nanosheet displays an excellent switching current ratio (9 × 102), a short rise and decay time (43 and 83 ms, respectively), and good stability (75% of the initial current after 90 days in air). In addition, the mechanical stability and flexibility of the photodetector on the flexible substrate are investigated for 500 bending cycles.

Tri-arm multipinhole interferometer for wavefront measurement and diffractive imaging.

We propose a tri-arm (or Y-shaped) multipinhole (MP) interferometer for wavefront measurement based on a specially designed tri-arm MP plate. We demonstrate that the complex amplitude of a wavefront sampled by the tri-arm MP plate inserted between the object and the detector plane can be extracted directly from the Fourier transform of a far-field diffraction intensity pattern without the need for any iterative algorithm. A form of coherent diffractive imaging based on a rotatable tri-arm MP plate is also demonstrated, which provides a feasible approach for lensless diffractive imaging in real time.

The effects of abscisic acid, salicylic acid and jasmonic acid on lipid accumulation in two freshwater Chlorella strains.

Sustainable renewable energy is being hotly debated globally because the continued use of finite fossil fuels is now widely recognized as being unsustainable. Microalgae potentially offer great opportunities for resolving this challenge. Abscisic acid (ABA), jasmonic acid (JA) and salicylic acid (SA) are involved in regulating many physiological properties and have been widely used in higher plants. To test if phytohormones have an impact on accumulating lipid for microalgae, ABA, JA and SA were used to induce two Chlorella strains in the present study. The results showed 1.0 mg/L ABA, 10 mg/L SA, and 0.5 mg/L JA, led strain C. vulgaris ZF strain to produce a 45%, 42% and 49% lipid content that was 1.8-, 1.7- and 2.0-fold that of controls, respectively. For FACHB 31 (number 31 of the Freshwater Algae Culture Collection at the Institute of Hydrobiology, Chinese Academy of Sciences), the addition of 1.0 mg/L ABA, 10 mg/L SA, and 0.5 mg/L, JA produced 33%, 30% and 38% lipid content, which was 1.8-, 1.6- and 2.1-fold that of controls, respectively. As for lipid productivity, 1.0 mg/L ABA increased the lipid productivity of C. vulgaris ZF strain and FACHB-31 by 123% and 44%; 10 mg/L SA enhanced lipid productivity by 100% and 33%; the best elicitor, 0.5 mg/L JA, augmented lipid productivity by 127% and 75% compared to that of controls, respectively. The results above suggest that the three phytohormones at physiological concentrations play crucial roles in inducing lipid accumulation in Chlorella.

Diffractive imaging based on a multipinhole plate.

We report on a noniterative method for coherent diffractive imaging based on a specially designed multipinhole (MP) plate. We demonstrated that the complex amplitude of the wavefront penetrating through an MP plate inserted between the specimen and the detector plane can be directly extracted from the Fourier transform of a single far-field diffraction intensity pattern without need of any iterative algorithm. A form of scanning diffractive imaging based on a rotatable MP plate is also demonstrated, which provides a feasible approach for lensless diffractive imaging of complex-valued objects.

Laplacian differential reconstruction of in-line holograms recorded at two different distances.

We analyze the diffraction of the picture obtained by the subtraction of two in-line holograms recorded in two planes at distances of z and z+Deltaz apart from the object plane. Our theoretical analysis reveals that the reconstructed field at the object plane is approximately equal to the Laplacian second-order differentiation of the object wave in transverse direction when Deltaz is much smaller than the distance z, that is, the reconstructed image presents a high quality of edge enhancement. We further investigate the dependence of the edge-enhancement quality on the longitudinal differential distance Deltaz and find that the reconstructed images have the sharpest edge-enhancement and high signal-to-noise ratio at the same time only when the value of Deltaz/z lies between 0.7% and 0.9% under our experimental condition. We also construct a criteria function, named the entropy of the image, to automatically focus the edge-enhanced image and demonstrate its adaptability in experiments.

Phase contrast Talbot array illuminators.

We propose a method for designing an improved phase-only Talbot array illuminator, called a phase contrast Talbot array illuminator (PCTAI), which could be used to generate an array of spots with a special intensity structure and high efficiency. As examples, we designed two types of PCTAIs for generating an array of line and hollow spots, respectively. Some experimental results revealing the phase contrast effect and demonstrating the feasibility of the PCTAIs are also given.