Fundus tessellation, commonly observed in individuals with myopia and among the elderly, represents a fundus alteration easily discernible and assessable. Long-term monitoring has revealed that fundus tessellation may persist unchanged for extended periods or progress, potentially leading to more severe fundus lesions and diminished visual quality. The clinical significance of fundus tessellation is not only as an early indicator and predictor of myopic macular degeneration(MMD), but also, to some extend, as a helpful assistance in early identification and mechanism research of the other ocular and systemic disease, including glaucoma, diabetic retinopathy, age-related macular degeneration, cognitive impairment, and Down syndrome. Currently, artificial intelligence(AI)has achieved remarkable results in detecting, grading, and quantifying fundus tessellation. Therefore, this paper discusses the ocular and systemic diseases related to changes in fundus tessellation, their underlying mechanisms, and advancements in AI-based identification and quantification of fundus tessellation, aiming to contribute to future research endeavors.