Despite its clinical effectiveness, PDT is currently underutilized because of the non-fully satisfied and expensive PS, unclear dose-efficiency relationship, and difficulties in translating proof-of-principle research. To further improve PDT efficacy, ongoing research is being pursued to develop the multifunctional nano-PS, wearable LED and self-excited light sources, and the spatiotemporal multimodal optical imaging platform for monitoring and optimizing dosimetric parameters for pre-, during-, and post-PDT.

The rapid development of NIR-Ⅱ fluorescence imaging technology provides new opportunities and means to solve the bottleneck problems in surgical navigation. With the cross-integration of material science, chemistry, and optics, a series of NIR-Ⅱ fluorescence surgical navigation molecular probes have been developed. However, these works are still in the stage of basic research and animal experiments. Clinical translation of these probes, which requires combined efforts from enterprises, hospitals, clinicians, and basic researchers, is yet to be promoted. Encouragingly, some preclinical studies have shown good clinical prospects, and laid a foundation for further promoting the translation and application of NIR-Ⅱ fluorescence surgery navigation. This will provide a strong guarantee for precision surgery in the future.

In summary, the application of ophthalmic laser technology covers various diseases of the anterior and posterior segments, from diagnosis to treatment. With the breakthrough of laser technology and increasing ophthalmology clinical demand, laser technology of diagnosis and treatment will be continuously optimized. This paper summarizes the applications of laser technology in the eye, and future challenges of different ophthalmology instruments, hoping to guide the breakthrough point of future technology.

R-32 with a low boiling point, high latent heat and a low GWP is promising to resplace R-134a and R-404A with high GWPs. Whereas the clinical potential in terms of cooling performance and laser attenuation is needed to be evaluated, and the complicated interaction mechanism between spray and lasers is urgent to be understood to optimize cooling parameters for clinicians. In this paper, the cooling performance and laser attenuation for R-134a, R-404A and R-32 are compared using the well-constructed transient CSC facility. Results demonstrate that three distinct stages of scattering by droplet, liquid film absorption and scattering by frost occurs in the variation of light transmittance. R-32 has the maximum surface heat flux (519.0 kW·m^-2), the shortest liquid film residence time (142 ms), and the least light attenuation under the irradiations of 755-nm and 1064-nm lasers owing to the low boiling point and large latent heat. The strong cooling capability, short liquid film residence time and small light attenuation of environment-friendly R-32 imply its good clinical application potential. But the clinical safety and feasibility of R-32 still requires the validation of clinical trials in patients, because of the absence of medical cryogens.

R404A can replace R134a due to its stronger cooling capacity in CSC. In this paper, the influence of spray distance and duration on the dynamic heat transfer of the R404A spray cooling is quantitatively investigated through experiments to analyze the mechanism of heat transfer under different conditions. The results show that increasing spray duration can prolong the cooling time of the liquid film; thus, improving the cooling protection of the skin. The maximum surface heat flux q_max and maximum heat transfer coefficient h_max decrease as the spray distance increases. It is worth noting that q_max changes slightly before 30 mm. Thus, the distance of 30 mm may be regarded as the optimal spray distance that obtains the lowest minimum temperature and relatively high heat flux. Finally, the dimensionless heat flux correlation is proposed based on theoretical analysis.

In this paper, we designed a dual-beam external differential interference eye-axis detection system with the Twyman-Green interferometric system architecture combined with digital signal processing technology to achieve low-coherence optical eye-axis length measurement. We implemented multiple measurements of the ZEISS standard analog eye axis and the human eye axis under the same conditions, the results showed that the eye-axis length measurement system designed in this paper had good validity and reliability. However, this system still had the error caused by the cooperation between the operator and the test subject during measurement, so we set the signal-to-noise ratio to >2.3 to ignore the interference of noise in the signal. In the next study, we will continue to optimize the signal processing method to improve the signal-to-noise ratio to enhance the accuracy of the measurements. This is necessary for accurate prediction of early pseudomyopia and myopia, their prevention and control, and to provide a technical solution for domestic AL measurement.

This study reveals the adaptive phenomenon in the fNIRS brain activation experiment and the factors that influence it. It is suggested that the research of BCI based on fNIRS also needs to consider adaptability. Since the activation level is not stable at the initial stage of the experiment, the magnitude of the amplitude change may influence the final feature extraction and classification effect. Therefore, it is necessary to conduct a period of pre-experiment and process the experimental data before the start of the experiment and wait for the amplitude to stabilize. If this characteristic is not considered, it will be difficult to extract the stable signal characteristics of fNIRS, which will greatly reduce the recognition accuracy of BCI. Although there are individual differences in this adaptability and it is not monotonously decreasing, this may involve more complex neural mechanisms. However, most people reach a relatively stable level after 3 d. This result suggests that we can consider using the data after 3 days of training when conducting the fNIRS-based brain-computer interface research. At the same time, the difference in training time requires that in the experimental process, the number of experimental days and daily experiment volume of each subject should have a certain consistency so as to eliminate the errors caused by different degrees of adaptation. Different paradigms have different adaptation time. Therefore, unless the effects of different difficulty paradigms are studied, it is necessary to ensure that the experimental paradigms are similar in difficulty to improve the efficiency of adaptive training and eliminate the errors of different paradigms.

In this study, the reconstruction ability of Bessel beam propagation through biological tissue is studied via simulation and experiment. The biological tissue is modeled as a turbulent medium with slight refractive index variations. By approximating weak scattering, Bessel beam generation and propagation in biological tissue are simulated using an algorithm that combines angular spectrum theory and step-by-step propagation method. On the experimental aspect, the Bessel beam generates flexibly with a SLM, providing a tool to adjust the Bessel beam parameters and verify the simulation result. A comparison between the simulation and the experimental results is carried out. The results show that after the phase disturbance of the biological tissue, the non-diffraction length of the reconstructed beam drastically reduces, and the reconstructed beam intensity is much lower than that of the original one. The thicker the biological tissue, the lower the reconstructed beam intensity. The bright spot radius of the zeroth-order Bessel beam changes oppositely with the axicon angle, but the cone angle of the axicon has little effect on the "non-diffraction length" of the reconstructed Bessel beam after passing through the biological tissue. The lower-order Bessel beams show better reconstruction ability from the perspective of retaining the cross-section light field intensity distribution. In addition, other experimental parameters, such as the spatial beam quality of Bessel beam and positions of biological tissues, will also affect the reconstruction characteristics of Bessel beam through biological tissues. The effects of these parameters can also be studied by using the theory and method in this paper.

In this paper, a brain tissue differential pathlength factor prediction model based on GS-SVM is established to quickly predict the DPF value of a brain tissue, and this method is compared with the BP-ANN prediction model. The results show that the grid optimization algorithm can automatically and accurately optimize the penalty parameter C and the parameter g of the Gaussian kernel function. The prediction results of the brain tissue differential pathlength factor prediction model based on GS-SVM are better than those based on BP-ANN, and have significant correlation with the prediction results of the Monte Carlo simulation method. It is expected to replace the Monte Carlo simulation method for batch calculation of DPF values. It can be applied in the near infrared cerebral oxygen monitoring instrument to make the calculation of physiological parameters of cerebral oxygen metabolism more rapid and accurate.

In this study, we investigated the effects of phototherapy on the learning and memory abilities of sleep-deprived mice by establishing a sleep deprivation model. We discovered that sleep deprivation significantly decreased the learning and memory abilities of mice and produced anxiety-like behaviors, while the combination of 468 nm blue light treatment prevented the increase of inflammatory response, improved the antioxidant capacity of hippocampal tissue, regulated the expression of BDNF-TrkB signaling pathway genes, enhanced inter-synaptic transmission, and effectively improved the learning and memory abilities of mice.

The use of the refractive index as an endogenous label in 3D quantitative imaging for label-free biological samples is gaining popularity. However, some of the following improvements still need to be made: 1) a more accurate scattering measurement model should be established to improve the imaging resolution at the theoretical level; 2) there is still a necessity to overcome the limitation of sparse data, develop a more effective refractive index 3D reconstruction inversion algorithm, and improve the reconstruction accuracy and calculation speed; 3) as the refractive index is nonspecific for biological features, in-depth analysis of the refractive index in samples is required. At the application level, this study requires mature equipment to advance clinical procedures. Furthermore, its applications can be expanded to other domains of study, including water environment monitoring, food safety, material characterization, virology, and single-molecule analysis.

We review several techniques of D-FFOCT suitable for metabolic activity visualization mechanisms in fundamental biology, precision medicine, and drug research. With advanced theories, ingenious algorithms, and latest optoelectronic devices, D-FFOCT may become a widely used, faster, and more convenient image method with an augmented label-free higher resolution and multi-contrast.

We developed an automatic QuanTi-FRET (AutoQT-FRET) method to measure the G and β factors by performing single imaging. The method for transfecting multiple plasmids in one cell dish reduces the time and shortens the process of calculating the correction factor G of the system. Simultaneously, the AutoQT-FRET method can classify cells transfected with multiple standard FRET plasmids in a cell petri dish. Thus, it enables the accurate measurement of the system correction factors G and β values using the one-button operation of one-time imaging of a cell petri dish, which greatly simplifies data processing and lowers the threshold for researchers who use quantitative FRET measurements. The AutoQT-FRET method is not only robust but also fast and concise.

This network proves the possibility of combining neural network and lensless computational microscopy in the field of cell classification, and greatly reduces the application cost of neural networks in cell classification. The cell data in this article only provides simple morphological information. We believe that, with the further improvement of the microscopy technology used, the improvement of data resolution can also bring a qualitative change to the classification accuracy of the network.

Considering a two-photon imaging system as an example, this paper verifies the effectiveness of the sFSC-based 3D image resolution evaluation method by comparing the results of the sFSC method with the theoretical calculation method and FWHM. Regarding image restoration, considering a confocal microscopic system as an example, the 3D PSF model obtained using sFSC results can be used for deconvolution image restoration. This restoration process can effectively retain the texture details and improve the 3D resolution. In Wiener filtering deconvolution image restoration, the lateral and the axial resolution of the reconstructed image are improved by 14.5% and 33.2%, respectively.

Accurate detection of different structures in biological tissues is of great significance for clinical applications. In this study, a fully polarized Mueller matrix imaging detector for biological tissues is constructed to investigate the distribution of different representation vectors of the same sample or similar structures of different tissues on the Poincare sphere. In the current study, the spherical and column scatterers represented by nucleus and fiber are studied. The characterization effect of the P and D vectors at a high magnification is found to be better than that at a low magnification. In terms of the difference of the P and D vectors between the two tissues, the difference for the fibrous connective tissue is >8% than that of the skeletal muscle tissue. In general, the P vector is generally 19.7% better than the D vector for obtaining the difference between two structures in a single biological tissue. Internal biological tissue microstructure changes tend to be small and difficult to detect. The experiment conducted in this study confirms that the Poincare sphere can be used to distinguish different structures of biological tissues; the minimum surrounded by different scatterer balls can realize effective determination of biological tissue microstructure and has certain clinical application potential.

This study proposes a dynamic SPI method for real-time data acquisition and a fast look-up table method for real-time data processing. The proposed dynamic SPI method effectively improves the frame rate without relying on the hardware performance of the imaging system. Combined with the circular sampling strategy and the optimization of measuring priority, the multi-wavelength spatial frequency diffuse images are dynamically measured at a sampling rate less than 1%. Moreover, a fast look-up table algorithm is developed, which performs region and pixel optimizations for the redundancy calculation of traditional look-up table methods. It effectively improves the efficiency of the look-up table method for optical property reconstruction. The proposed method realizes real-time acquisition and reconstruction of the multi-wavelength optical property images for more than 10 frames per second. This provides an effective technical scheme for real-time implementation of single-pixel SFDI.

In this paper, we describe an innovative PACT image reconstruction algorithm based on DI-Net, a dual-domain neural network. Both numerical simulations and in vivo experiments are used to evaluate the performance of the proposed DI-Net. The imaging results reveal that DI-Net can effectively suppress streak-type artifacts caused by undersampling and the reconstructed images are comparable with the reference image. The imaging results also demonstrate that the proposed DI-Net provides better image quality compared with the widely-used FBP algorithm and the popular Post-Unet algorithm.

In this study, we used a high-sensitivity multichannel fNIRS system based on the lock-in photon-counting technique to detect signals in the human brain by employing the full parallel excitation method. We used the original light intensity and hemoglobin concentration data to construct the SVM model to recognize subjects’ "positive/negative" binary intention. The average classification accuracies of the original light intensity data and hemoglobin concentration change data were 70.6%±3.7% and 73.1%±1.7%, respectively. Therefore, we demonstrated the ability of the high-sensitivity multichannel fNIRS system to directly detect the "positive/negative" binary intention of the human brain. The findings of this study provide a useful idea for applying fNIRS-BCI in clinical applications and daily lives, such as helping patients with locked-in syndrome express their intention more directly and developing a more convenient brain-controlled smart home.

This paper proposes the optical and physiological parameter extraction of human skin tissue based on the SFDI method.The camera collects the backscattered light of samples or tissues, obtains the optical parameters by diffusion theory, and inverts the physiological parameters by nonlinear least square method and minimum error criterion. In vivo and in vitro experimental results show that the proposed method can be used to measure tissue oxygen saturation. This verifies the accuracy of optical and physiological parameters extracted using the system. It also provides a new suitable method for noninvasive and fast detection of related diseases.

In this paper, we describe an innovative PACT image reconstruction algorithm based on DI-Net, a dual-domain neural network. Both numerical simulations and in vivo experiments are used to evaluate the performance of the proposed DI-Net. The imaging results reveal that DI-Net can effectively suppress streak-type artifacts caused by undersampling and the reconstructed images are comparable with the reference image. The imaging results also demonstrate that the proposed DI-Net provides better image quality compared with the widely-used FBP algorithm and the popular Post-Unet algorithm.