Yanwu Xu

A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images.

The results demonstrate the potential of the deep learning system for angle-closure detection in AS-OCT images.

Digital Gonioscopy Based on Three-dimensional Anterior-Segment OCT: An International Multicenter Study.

The 3D DGS is effective in detecting eyes with suspected PACG. It has the potential to be used widely in the primary eye care community for screening of subjects at high risk of developing PACG.

A Retrospective Comparison of Deep Learning to Manual Annotations for Optic Disc and Optic Cup Segmentation in Fundus Photographs.

We demonstrated the potential of the deep learning system to assist ophthalmologists in analyzing OD and OC segmentation and discriminating glaucoma from nonglaucoma subjects based on CDR calculations.

A Multicenter Clinical Study of the Automated Fundus Screening Algorithm.

Automated fundus screening software demonstrated a high sensitivity and specificity in detecting RDR, GCS, and RMD from color fundus imaged captured using various cameras.

Enhancing Glaucoma Diagnosis Through Multi-Layer Transformer and Multi-Modal Feature Fusion.

The proposed multi-modal-based glaucoma grading framework offers a more accurate diagnostic tool by integrating multiple examination modalities and prior knowledge, representing a substantial improvement over existing single-modality-based systems.