Optical coherence tomography angiography(OCTA)is a non-invasive imaging technique that provides three-dimensional,informative vascular images.Numerous studies have shown that OCTA technology has unique advantages in biomarker quantification,diagnosis and monitoring,and has therefore been rapidly applied in experiments and clinical stud-ies.Image analysis tools can quickly and accurately quantify vascular and pathological features,greatly improving the value of OCTA imaging.In recent years,artificial intelligence(AI)has become the most powerful image analysis method,espe-cially deep learning-based image analysis,which can provide accurate measurements in various situations,including differ-ent diseases and eye regions.The Ophthalmic Imaging and Intelligent Medicine Branch of Chinese Medicine Education Asso-ciation and the Ophthalmology Committee of International Association of Translational Medicine designated experts to sum-marize the application of AI in OCTA image analysis and disease diagnosis at home and abroad,including accurate detection of choroidal neovascularization and other lesions,accurate quantification of retinal perfusion,and reliable disease diagno-sis.They also analyzed the current challenges and development directions.After multiple rounds of discussion and revi-sions,they drafted the guidelines for the application of AI in OCTA image analysis and ocular disease diagnosis,aiming to provide new insights and references for clinical practice.

The accuracy of ultrasound examination and measurement is of great significance to diagnosing ocular disea-ses.The commonly used ocular ultrasonography includes amplitude(A)-mode ultrasound,brightness(B)-mode ultra-sound,ultrasound biomicroscopy(UBM),and color Doppler flow imaging(CDFI).A-mode ultrasound is mainly used to measure the distance between tissues with different echo intensities.B-mode ultrasound can visualize the two-dimensional structure of the eye and make quantitative measurements of the target point.UBM is an ultra-high-frequency two-dimen-sional imaging method,which can clearly display the structural characteristics of the anterior segment and measure the rele-vant parameters.It can also help quantitatively analyze the morphological changes of the angle and the anterior segment be-fore and after implantable collamer lens surgery.CDFI can quantitatively measure the parameters of blood vessels by apply-ing the Doppler effect on the basis of two-dimensional ultrasound,reflecting the changes of blood flow in the eye.To standardize the operations of different ultrasound examination methods,this guideline is formulated.This guideline mainly focuses on the standardized operation of ocular ultrasound instruments and their clinical application in ocular diseases,so as to provide guidance for the diagnosis and treatment of related ocular diseases.

Senile macular degeneration(SMD)is a complex,highly heritable,and multifactorial disease that leads to the aging-related change in the macular region,characterized by progressive retinal degeneration and progressive loss of vi-sion.About 200 million people worldwide suffer from SMD,and the incidence is increasing as the population ages.Artifi-cial intelligence(AI)technology has developed rapidly in recent years,and its application in the medical field has brought new possibilities for the development of the medical industry.AI-based qualitative and quantitative evaluation of retinal fluid can not only facilitate the diagnosis of neovascular SMD but also help adjust the treatment plan timely according to the effect,so as to provide more targeted treatment for patients.This guide summarizes the application of AI in the treatment of SMD,including the application progress,clinical application and future development of AI in retinal fluid monitoring,to pro-vide sufficient support for ophthalmologists to evaluate patient's conditions,design treatment plans and estimate prognosis.

The rapid development of artificial intelligence(AI)technology has driven the intelligentization of medicine.In recent years,due to the continuous improvement of machine learning and deep learning technologies,AI technology has made rapid progress in the diagnosis and treatment of ocular fundus diseases,including retinal vascular disease,macular disease,retinal detachment,and retinal pigment degeneration.Early diagnosis and treatment are of great significance for the prognosis of ocular fundus diseases.This article gives a guide for the application of AI in automatic segmentation of ret-inal images and disease diagnosis,providing a reference for further research and appIication of AI in this field.