Objective: To obtain the comprehensive information of the anterior eye image, establish complementary information for the diagnosis and evaluation of ocular diseases. Methods: We developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Results: The uHR-OCT module achieved an axial resolution of approximately 2 μm in tissues. The lateral resolution of the ocular surface microvascular imaging module under maximum magnification was approximately 3.5 μm. By combining the imaging optical paths of different modules, the customized multi-modal eye imaging platform was capable of performing real-time cross-sectional UHR-OCT imaging of the anterior eye, conjunctival vessel network imaging, high-resolution conjunctival blood flow videography, and traditional slit-lamp imaging on a single device. With self-developed software, a conjunctival vessel network image and blood flow videography were further analyzed to acquire quantitative morphological and hemodynamics parameters, including vessel fractal dimensions, blood flow velocity and vessel diameters. Conclusion: The ability of the multi-modal anterior eye imager to provide both structural and functional information for ophthalmic clinical applications can be demonstrated in a healthy human subject and a keratitis patient.

Objective: To analyze the morphological characteristics of meibomian glands in human eyes and to explore the application research of meibomian glands analysis system in ocular surface diseases. Methods: A total of 24 healthy subjects were recruited by Zhongshan Ophthalmic Center to infrared photography of meibomian glands. Ten of healthy subjects were selected by the two operators for infrared photography of meibomian glands on the same model of equipment. The images were repeatedly measured and analyzed by the self-designed analysis software on the morphological measurements of the five glands in the center of the upper eyelid. Results: The measured biological parameters are shown below: the average gland diameter was (0.48±0.09) mm, the average gland length was (5.25±0.68) mm, the average gland area was (2.12±0.53) mm, the gland deformation coefficient was 10.01±3.85, the development value was 6.32±1.23, the percentage of the five central glands in the central area was (10.94±2.20)%, and the glands accounted for (58.07±8.13)% of the upper conjunctiva area. There was no statistical difference between the two measurements of each index (P>0.05). Repeatability analysis results showed that coefficients of variation (CV) of all biological parameters of glands were less than 5% and the intraclass correlation coefficient (ICC) in both groups were greater than 0.95. Conclusion: The Meibomian Gland Bioimage Analyzer provides good reliability and consistency for morphological measurements of the meibomian gland, and it is expected to provide new non-invasive indicators for clinical assessment of the meibomian glands function.

Objective: This study was designed to explore its potential value for new medical service model based on the intelligent voice follow-up system and analyze its application effect during the outbreak of COVID-19. The actual effectiveness of this intelligent voice follow-up system applied in the Internet hospital to carry out medical consultation service was discussed. Methods: In this study, an intelligent voice follow up system was developed for postoperative follow-up of children with congenital cataract. First, a well-designed and structured questionnaire contents were developed for postoperative follow-up. Secondly, the intelligent voice follow-up system was deployed. The system would automatically jump to the next follow-up step according to the user’s response, and give appropriate suggestions. Finally, the data of telephone recording, call time, children’s attributes were collected and statistically analyzed. Results: From February 24 to March 15, 2020, 561 families of children with congenital cataract from Zhongshan Ophthalmic Center were recruited by using the intelligent voice follow-up system. The system completed a total of 1 154 calls, of which 561 cases received follow-up data, reaching an average effective call rate of 48.6%. Among 561 cases, 204 (36.4%) thought that the extended time of follow-up visit would affect the recovery of children, while 309 (55.1%) thought that it exerted no effect on the recovery. 360 children (64.2%) achieved good ocular recovery without complications, whereas 169 cases (30.1%) developed ocular symptoms. These include white spots in the pupil area, redness and eye secretions. Statistics of different behavior of children showed that there were 417 (74.3%) children wearing glasses, 135 (24.1%) children did not wear glasses, another 9 (1.6%) children wearing glasses were not clear, often rubbing the eyes of children were more likely to appear redness (20.4%), eye secretions (17.0%) and white spots in the pupil area (6.8%) and other adverse reactions. Conclusion: The intelligent voice follow-up system shows great application potential in clinical follow-up, which can be employed as a new service mode of intelligent medical treatment.

Objective: Due to the limitations of small imaging field of view of in vivo confocal microscopy (IVCM) or the incapability of cellular imaging of traditional optical coherence tomography (OCT) in human corneal imaging, this study was designed to develop a novel high-resolution in vivo human corneal imaging system based on full-field OCT (FFOCT). Methods: The FFOCT system utilized a high numerical aperture air immersion microscope objective and a high-speed area array CMOS camera with two-phase modulation image processing algorithm to achieve high-speed high-resolution non-contact imaging of human cornea. To verify its feasibility, in vivo cornea imaging at different depth was performed on a healthy human subject. Results: The FFOCT system achieved a theoretical lateral imaging resolution of 1.7 μm, an imaging field of view of 1.26 mm×1.26 mm, and an imaging rate of 275 Hz/s. High-resolution FFOCT images of the main structural layers of cornea were achieved by imaging a healthy human cornea in vivo with this system in a non-contact way. Conclusion: The FFOCT human corneal imaging system combines the advantages of the non-contractness and the large imaging field of view of traditional OCT with the cellular lateral resolution of IVCM, potentially providing a new imaging system for the research and clinical diagnosis and treatment of corneal diseases.

Objective: To achieve the segmentation of different layers and fluid areas on the optical coherence tomography (OCT) image of the retina. Methods: A lightweight neural network based on deep learning was proposed. The network structure adopted in this study was designed based on the architecture of dilated-residual U-Net. By connecting the upsampling output obtained at different depth networks, multi-scale feature fusion was performed to enable the system to accurately identify the boundaries on the OCT image. Results: Compared with U-Net, this algorithm could achieve the same accuracy with 1–2 epochs less, and the accuracy was also improved by 1.25%. Conclusion: The proposed network improves the segmentation performance of retinal OCT images, and reduces the number of parameters, which demonstrates the network has great application potential.

Objective: To evaluate the effectiveness of an artificial intelligence-assisted diagnostic system for cataract screening in community. Methods: A prospective observational study was carried out based on a telemedicine platform. Patient history, medical records and anterior ocular segment images were collected and transmitted from community healthcare centers to Zhongshan Ophthalmic Center for evaluation by both ophthalmologists and artificial intelligence-assisted cataract diagnostic system. Results: Of all enumerated subjects, 35.7% were male and the median age was 66 years old. Of all enumerated slit-lamp images, 98.7% met the requirement of acceptable quality. This artificial intelligence-assisted diagnostic system achieved an AUC of 0.915 for detection of severe cataracts in the external validation dataset. For subjects who were advised to be referred to tertiary hospitals by doctors, 80.3% of them received the same suggestion from this artificial intelligence-assisted diagnostic system.Conclusion: This artificial intelligence-assisted cataract diagnostic system showed high applicability and accuracy in community-based cataract screening and could be a potential model of care in community-based disease screening.

The application of artificial intelligence technology in ophthalmology has been on the agenda, and has continued to progress in practice, such as the application of big data, image information analysis, the era of robotics, and now it is on a new step to promote the accuracy of biometrics. These are protections for the visual organs and the vision, make they have normal visual function, and display unique characteristic of visual information. The “eye and artificial intelligence” has continuously opened up new fields and achieved new successes.

Rhegmatogenous retinal detachment (RRD) is a kind of serious vision-threatening eye diseases. The mainly management is surgical, including pneumatic retinopexy (PR), scleral buckling (SB), and pars plana vitrectomy (PPV). So far, no concensus has been reached regarding the chioce of these interventions, for which it is clinically significant to study and make a strategy for choosing the optimal surgery. Furthermore, the formulation of the surgical plan for RRD patients in bed is usually related to clinical factors such as age, duration of retinal detachment, hole type, number, location and size of the holes, etc. This paper reviews clinical factors that affect the choice of surgery for RRD.

dry eye is one of the most common eye diseases caused by multiple factors. With the increasing incidence of dry eye year by year, dry eye gradually attracts people's attention. The pathogenesis of dry eye is complex, including aging, inflammation, cataract surgery, secondary local ocular surface diseases, and systemic diseases. Ocular surface inflammation is the most critical link in the pathogenesis of dry eye, and a variety of inflammatory mediators and immune cells are involved in the process. The comprehensive treatment of dry eye includes changes in the eye environment and etiology. Cyclosporine A (CsA), an immunosuppressant that treats this inflammation by improving tear quality, has been shown to be effective in the treatment of dry eyes, but its clinical use is limited due to its poor water solubility and low ocular availability. Therefore, this paper reviews the application of cyclosporine A in dry eye, analyzes the latest views and research hotspots, and provides reference for the treatment of dry eye.

In recent years, ectopia lentis has gradually attracted the attention of ophthalmologists, and the exploration and improvement of surgery for ectopia lentis has been in progress. With the invention of phacoemulsification technology and the improvement of intraocular implant materials, the implantation and fixation of intraocular lens (IOL) in patients with ectopia lentis has become the focus of ophthalmologists. Suspensory IOL implantation is a classic operation for IOL implantation in patients with severe lens dislocation or aphakia with insufficient capsular bag support. It has mainly gone through three stages: traditional trans-sclera suture-fixed posterior chamber IOL, kontless posterior chamber IOL fixation represented by Z suture, and sutureless intrascleral IOL fixation. Understanding and mastering the advantages and limitations of various IOL fixation methods is of great importance for improving the diagnosis and treatment level of ophthalmologists and as well as the prognosis of patients.