Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD.
Diagnostics (Basel, Switzerland)（2023）
This report describes a novel high performance DL-based model for the detection and measurement of . This biomarker showed promising results in predicting progression in nonexudative AMD patients.更多
age-related macular degeneration,automated feature segmentation,clinical trial selection,deep learning,ellipsoid zone integrity,geographic atrophy,photoreceptor damage,progression prediction,quantitative optical coherence tomography