关键词: 晚期青光眼, 视神经, 视网膜神经纤维层, 视网膜血管密度, 人工智能

Abstract: Advanced glaucoma is characterized by severe visual field defects and deterioration of visual acuity. Precise dynamic monitoring of disease progression is crucial for delaying vision loss. Conventional diagnostic modalities, including optical coherence tomography and perimetry, exhibit reduced reliability in advanced-stage patients due to the "floor effect" and poor patient compliance.Recent advances in imaging technologies (e.g., optical coherence tomography angiography) and functional testing techniques (e.g., full-field electroretinography, microperimetry) have provided new approaches for monitoring advanced glaucoma. Particularly, the integration of artificial intelligence technologies (e.g., generative adversarial networks, convolutional neural networks) has significantly enhanced the accuracy and efficiency of detection.

Key words: Advanced glaucoma, Optic nerve, Retinal nerve fiber layer, Retinal vascular density, Artificial intelligence