Improved nested U-structure for accurate nailfold capillary segmentation.

Changes in the structure and function of nailfold capillaries may be indicators of numerous diseases. Noninvasive diagnostic tools are commonly used for the extraction of morphological information from segmented nailfold capillaries to study physiological and pathological changes therein. However, current segmentation methods for nailfold capillaries cannot accurately separate capillaries from the background, resulting in issues such as unclear segmentation boundaries. Therefore, improving the accuracy of nailfold capillary segmentation is necessary to facilitate more efficient clinical diagnosis and research. Herein, we propose a nailfold capillary image segmentation method based on a U2-Net backbone network combined with a Transformer structure. This method integrates the U2-Net and Transformer networks to establish a decoder-encoder network, which inserts Transformer layers into the nested two-layer U-shaped architecture of the U2-Net. This structure effectively extracts multiscale features within stages and aggregates multilevel features across stages to generate high-resolution feature maps. The experimental results demonstrate an overall accuracy of 98.23 %, a Dice coefficient of 88.56 %, and an IoU of 80.41 % compared to the ground truth. Furthermore, our proposed method improves the overall accuracy by approximately 2 %, 3 %, and 5 % compared to the original U2-Net, Res-Unet, and U-Net, respectively. These results indicate that the Transformer-U2Net network performs well in nailfold capillary image segmentation and provides more detailed and accurate information on the segmented nailfold capillary structure, which may aid clinicians in the more precise diagnosis and treatment of nailfold capillary-related diseases.

Fast Fourier ptychographic quantitative phase microscopy for in vitro label-free imaging.

Quantitative phase microscopy (QPM) is indispensable in biomedical research due to its advantages in unlabeled transparent sample thickness quantification and obtaining refractive index information. Fourier ptychographic microscopy (FPM) is among the most promising QPM methods, incorporating multi-angle illumination and iterative phase recovery for high-resolution quantitative phase imaging (QPI) of large cell populations over a wide field of-view (FOV) in a single pass. However, FPM is limited by data redundancy and sequential acquisition strategies, resulting in low imaging efficiency, which in turn limits its real-time application in in vitro label-free imaging. Here, we report a fast QPM based on Fourier ptychography (FQP-FPM), which uses an optimized annular downsampling and parallel acquisition strategy to minimize the amount of data required in the front end and reduce the iteration time of the back-end algorithm (3.3% and 4.4% of conventional FPM, respectively). Theoretical and data redundancy analyses show that FQP-FPM can realize high-throughput quantitative phase reconstruction at thrice the resolution of the coherent diffraction limit by acquiring only ten raw images, providing a precondition for in vitro label-free real-time imaging. The FQP-FPM application was validated for various in vitro label-free live-cell imaging. Cell morphology and subcellular phenomena in different periods were observed with a synthetic aperture of 0.75 NA at a 10× FOV, demonstrating its advantages and application potential for fast high-throughput QPI.

Fast digital refocusing Fourier ptychographic microscopy method based on convolutional neural network.

Fourier ptychographic microscopy (FPM) is used to achieve high resolution and a large field of view. However, traditional FPM image reconstruction methods often yield poor image quality when encountering out-of-focus issues during reconstruction. Therefore, this study proposes a defocus-distance regression network based on convolutional neural networks. In an experimental validation, the root-mean-square error calculated from 1000 sets of predicted and true values was approximately 6.2 µm. The experimental results suggest that the proposed method has good generalization, maintains high accuracy in predicting defocus distances even for different biological samples, and extends the imaging depth-of-field of the FPM system by a factor of more than 3.

Fast and robust Fourier ptychographic microscopy with position misalignment correction.

Significance: Fourier ptychographic microscopy (FPM) is a new, developing computational imaging technology. It can realize the quantitative phase imaging of a wide field of view and high-resolution (HR) simultaneously by means of multi-angle illumination via a light emitting diode (LED) array, combined with a phase recovery algorithm and the synthetic aperture principle. However, in the FPM reconstruction process, LED position misalignment affects the quality of the reconstructed image, and the reconstruction efficiency of the existing LED position correction algorithms needs to be improved. Aim: This study aims to improve the FPM correction method based on simulated annealing (SA) and proposes a position misalignment correction method (AA-C algorithm) using an improved phase recovery strategy. Approach: The spectrum function update strategy was optimized by adding an adaptive control factor, and the reconstruction efficiency of the algorithm was improved. Results: The experimental results show that the proposed method is effective and robust for position misalignment correction of LED arrays in FPM, and the convergence speed can be improved by 21.2% and 54.9% compared with SC-FPM and PC-FPM, respectively. Conclusions: These results can reduce the requirement of the FPM system for LED array accuracy and improve robustness.

Automated nailfold capillary density measurement method based on improved YOLOv5.

Nailfold capillary density is an essential physiological parameter for analyzing nailfold health; however, clinical images of the nailfold are taken in many situations, and most clinicians subjectively analyze nailfold images. Therefore, based on the improved "you only look once v5" (YOLOv5) algorithm, this study proposes an automated method for measuring nailfold capillary density. The improved technique can effectively and rapidly detect distal capillaries by incorporating methods or structures such as 9mosaic, spatial pyramid pooling cross-stage partial construction, bilinear interpolation, and efficient intersection over union. First, the modified YOLOv5 algorithm was used to detect nailfold capillaries. Subsequently, the number of distal capillaries was filtered using the 90° method. Finally, the capillary density was calculated. The results showed that the Average Precision (AP)@0.5 value of the proposed approach reached 85.2 %, which was an improvement of 4.93 %, 5.24 %, and 107 % compared with the original YOLOv5, YOLOv6, and simple-faster rapid-region convolutional network (R-CNN), respectively. For different nailfold images, using the density calculated by nailfold experts as a benchmark, the calculated results of the proposed method were consistent with the manually calculated results and superior to those of the original YOLOv5.

Multi-level optical angiography for photodynamic therapy.

Blood flow imaging is widely applied in photodynamic therapy (PDT) to provide vascular morphological and statistical parameters. This approach relies on the intensity of time-domain signal differences between blood vessels and background tissues; therefore, it often ignores differences within the vasculature and cannot accommodate abundant structural information. This study proposes a multi-level optical angiography (MOA) method for PDT. It can enhance capillaries and image vessels at different levels by measuring the signal frequency shift associated with red blood cell motion. The experimental results regarding the PDT-induced chorioallantoic membrane model showed that the proposed method could not only perform multi-level angiography but also provide more accurate quantitative information regarding various vascular parameters. This MOA method has potential applications in PDT studies.

Adaptive correction method of hybrid aberrations in Fourier ptychographic microscopy.

Significance: Fourier ptychographic microscopy (FPM) enables quantitative phase imaging with a large field-of-view and high resolution by acquiring a series of low-resolution intensity images corresponding to different spatial frequencies stitched together in the Fourier domain. However, the presence of various aberrations in an imaging system can significantly degrade the quality of reconstruction results. The imaging performance and efficiency of the existing embedded optical pupil function recovery (EPRY-FPM) aberration correction algorithm are low due to the optimization strategy. Aim: An aberration correction method (AA-P algorithm) based on an improved phase recovery strategy is proposed to improve the reconstruction image quality. Approach: This algorithm uses adaptive modulation factors, which are added while updating iterations to optimize the spectral function and optical pupil function updates of the samples, respectively. The effectiveness of the proposed algorithm is verified through simulations and experiments using an open-source biological sample dataset. Results: Experimental results show that the proposed AA-P algorithm in an optical system with hybrid aberrations, recovered complex amplitude images with clearer contours and higher phase contrast. The image reconstruction quality was improved by 82.6% when compared with the EPRY-FPM algorithm. Conclusions: The proposed AA-P algorithm can reconstruct better results with faster convergence, and the recovered optical pupil function can better characterize the aberration of the imaging system. Thus, our method is expected to reduce the strict requirements of wavefront aberration for the current FPM.

Suppression of coupling between optical aberration and tilt-to-length noise in a space-based gravitational wave telescope.

Coupling between exiting wavefront error of space gravitational wave telescopes and tilt-to-length (TTL) noise affects the measurement accuracy. Using the LISA Pathfinder signal, we analyzed cancellation and superposition of TTL coupling noise under various optical aberrations. We proposed proportion requirements of any two aberrations amplitude when noise was cancelled and an aberration amplitude control requirement when noise was superposed. Taking them as the aberration control requirements of gravitational wave telescope optical system, the exiting wavefront error requirements was reduced while suppressing the TTL coupling noise. A 40× optical telescope system with detection aperture φ=200 mm was designed. The exiting wavefront error was relaxed from 0.02 λ to 0.0496 λ. The maximum coupling coefficient value did not exceed 6.9448 pm/µrad within a pointing jitter angle of ±300 µrad. The proposed approach should be useful in future telescope design.

Hybrid enhancement algorithm for nailfold images with large fields of view.

Collecting and analyzing human nailfold images is an important component of studying human microcirculation. However, the large-field-of-view and high-resolution nailfold images captured by research microscopes introduce issues such as uneven brightness, low imaging contrast, and unclear vascular contours. To overcome these issues, this paper proposes a hybrid enhancement algorithm for nailfold images with large fields of view. First, adaptive histogram equalization with limited contrast (Clahe) is used to redistribute gray levels to enhance the brightness and contrast of images. Next, nonlocal means denoising (NL-means) is used to remove the noise amplified by Clahe algorithm. Finally, unsharp masking (Usm) is used to enhance the edge contour information of nailfold blood vessels. Comparing the enhanced images reveals that the hybrid enhancement algorithm improves the brightness and contrast of the nailfold image, makes the nailfold vessel contour more obvious, and the image noise continues to remain small, and it obtains the best visual effect. It is superior to other algorithms in terms of objective indicators and subjective evaluation.

Reduction in required volume of imaging data and image reconstruction time for adaptive-illumination Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) is a promising super-resolution computational imaging technology. It stitches a series of low-resolution (LR) images in the Fourier domain by an iterative method. Thus, it obtains a large field of view and high-resolution quantitative phase images. Owing to its capability to perform high-spatial bandwidth product imaging, FPM is widely used in the reconstruction of conventional static samples. However, the influence of the FPM imaging mechanism limits its application in high-speed dynamic imaging. To solve this problem, an adaptive-illumination FPM scheme using regional energy estimation is proposed. Starting with several captured real LR images, the energy distribution of all LR images is estimated, and select the measurement images with large information to perform FPM reconstruction. Simulation and experimental results show that the method produces efficient imaging performance and reduces the required volume of data to more than 65% while ensuring the quality of FPM reconstruction.

Fast and stable Fourier ptychographic microscopy based on improved phase recovery strategy.

Fourier ptychographic microscopy (FPM) imaging is a computational imaging technology that can reconstruct wide-field high-resolution (HR) images. It uses a series of low-resolution images captured by a camera under different illumination angles. The images are stitched in the Fourier domain to expand their spectral range. Under high-angle illumination, a dark-field image is noisy with a low signal-to-noise ratio, which significantly reduces the reconstruction quality of FPM. Conventional reconstruction algorithms often have low FPM imaging performance and efficiency due to optimization strategies. In response to these problems, this paper proposes an FPM imaging method based on an improved phase recovery strategy to optimize the alternating iterative algorithm. The technique uses an improved threshold method to reduce noise in the image preprocessing stage to maximize the retention of high-frequency sample information. Moreover, an adaptive control factor is added in the subsequent iterative update process to balance the sample spectrum function. This study verifies the effectiveness of the proposed method on both simulation and experimental images. The results show that the proposed method can effectively suppress image background noise and has a faster convergence speed and higher robustness. In addition, it can be used to reconstruct HR complex amplitude images of objects under wide field-of-view conditions.

Rapid qualitative and quantitative determination of food colorants by both Raman spectra and Surface-enhanced Raman Scattering (SERS).

Surface Enhanced Raman Scattering (SERS) spectroscopy technology is widely used in materials analysis, environmental monitoring, biomedical, food security and other fields. Flower-shaped silver nanoparticles have been successfully synthesized by a simple aqueous phase silver nitrate reduction by ascorbic acid in the presence of polyvinylpyrrolidone (PVP) surfactant. The nanoparticles diameters were adjusted from 450 to 1000nm with surface protrusions up to 10-25nm. The flower-shaped silver nanostructures obtained were used as stable SERS substrates with high SERS activity for detecting Rhodamine 6G (R6G), at a concentration of only 10-9mol/L, where the SERS signal is still clear. SERS spectroscopy of four different food colorants (e.g. food blue, tartrazine, sunset yellow, acid red) were analysed and the characteristic bands were identified. An improved principle component analysis (PCA) was used for four different food colorants detection, at concentrations down to about 10-8mol/L. Thus, the LOD of food blue, tartrazine, sunset yellow and acid red are 79.285µg/L, 5.3436µg/L, 45.238µg/L and 50.244µg/L, respectively.

Design of a silver nanoparticle for sensitive surface enhanced Raman spectroscopy detection of carmine dye.

Flower-shaped silver nanoparticles have been successfully synthesized by a simple aqueous phase silver nitrate reduction by ascorbic acid in the presence of polyvinylpyrrolidone (PVP) surfactant. The nanoparticles diameters were adjusted from 450 to 1000nm with surface protrusions up to 10-25nm. The growth direction of silver nuclei is controlled by their degree of coating by PVP. The flower-shaped silver nanostructures obtained were used as stable Surface Enhanced Raman Scattering (SERS) substrates with high SERS activity for detecting Rhodamine 6G (R6G), at a concentration of only 10-9M, where the SERS signal is still clear. SERS spectra of the dye carmine was analysed and the characteristic bands were identified. An improved principle component analysis (PCA) was used for carmine detection, at concentrations down to 10-8M. The characteristic peaks of the carmine (1019, 1360, and 1573cm-1) remained at 10-8M. This indicated that the minimum detection limit of AgNP-based substrate for carmine is about 10-8M.

Quantitative Analysis of Mg, Fe and Ca in Jade with Laser Induced Breakdown Spectroscopy.

Based on laser induced breakdown spectroscopy and X-ray fluorescence spectroscopy, The calibration curve of the main elements Mg, Cr and trace element Fe in the Jade samples is obtained based on experimental results. In the experiment, LIBS experiment conditions were 3 µs delay, 110 accumulated laser pulse, 100 mJ·pulse-1, 10 Hz pulse repetition frequency, plasma in Nanyang jade was induced using nono-second Nd∶YAG (wavelength: 1 064 nm) laser as the excitation source in the atmosphere envtronment of the laboratory. The spectral lines in the 300~1 000 nm wavelength range have been identified with the laser-induced breakdown spectroscopy. Through comparing the characteristic spectrum with the National Institute of standards and Technology Research Institute (NIST) database, the element of Mg, Ca and Fe are found in the Jade samples. Using the X-ray fluorescence spectra analyzed the metal elements Mg, Cr and Fe in Nanyang standard jade and obtained the content of elemental oxides, taking the content as standard data and selecting the high content element Al as internal standard element. According to LIBS calibration curve, we can calculate the content of 3 elements in the measured sample. The result shows that the concentration of elements locate in their corresponding standards range, for example, go(0.28%~1.73%), and Fe2O3 (0~0.8%), CaO ( 18%~20%).Because of its unique features, like the absence of sample preparation, the ability to perform real-time, and in situ analysis as well as the quasi non-destruction and micro-analysis character of the measurements, so as to verify the feasibility of LIBS application in jade.

Multiregion apodized photon sieve with enhanced efficiency and enlarged pinhole sizes.

A novel multiregion structure apodized photon sieve is proposed. The number of regions, the apodization window values, and pinhole sizes of each pinhole ring are all optimized to enhance the energy efficiency and enlarge the pinhole sizes. The design theory and principle are thoroughly proposed and discussed. Two numerically designed apodized photon sieves with the same diameter are given as examples. Comparisons have shown that the multiregion apodized photon sieve has a 25.5% higher energy efficiency and the minimum pinhole size is enlarged by 27.5%. Meanwhile, the two apodized photon sieves have the same form of normalized intensity distribution at the focal plane. This method could improve the flexibility of the design and the fabrication the apodized photon sieve.

Fast and accurate focusing analysis of large photon sieve using pinhole ring diffraction model.

In this paper, we developed a pinhole ring diffraction model for the focusing analysis of a large photon sieve. Instead of analyzing individual pinholes, we discuss the focusing of all of the pinholes in a single ring. An explicit equation for the diffracted field of individual pinhole ring has been proposed. We investigated the validity range of this generalized model and analytically describe the sufficient conditions for the validity of this pinhole ring diffraction model. A practical example and investigation reveals the high accuracy of the pinhole ring diffraction model. This simulation method could be used for fast and accurate focusing analysis of a large photon sieve.

Simplified transformation circle theory in analyzing a laser resonator.

Transformation circle theory is simpler than other methods for analyzing laser resonators. In our analysis only sigma circles and simple mathematical knowledge are used to analyze the stability and calculate the parameters of the laser resonator, which further simplifies the transformation theory. The results agree well with the well-known matrix theory. Two- and three-mirror (including a thermal lens) laser resonators are used as examples to present the stability formula and the Gaussian beam dimensions at the mirrors. Furthermore, we apply the commonly used example in which the laser medium is close to the cavity mirror.