Visual Field

Visual field assessment quantifies the extent of a person's vision, crucial for diagnosing conditions like glaucoma and myopia. Current research focuses on improving the accuracy and efficiency of visual field testing, employing machine learning models (including convolutional neural networks and geometric deep learning) to analyze fundus photographs, optical coherence tomography scans, and even patient responses during perimetry. These advancements aim to create faster, more objective, and patient-friendly diagnostic tools, ultimately improving the detection and management of vision-impairing diseases. The integration of biomechanical data with structural information is also showing promise in enhancing predictive models of visual field loss.