Deep Learning-Based Automated Segmentation and Multi-Parametric Quantitative Assessment of the Lacrimal Drainage System on CT-DCG.

The proposed deep learning framework demonstrates the technical feasibility of automated segmentation and morphological quantification of the lacrimal sac and bony nasolacrimal duct on CT dacryocystography.

Although further prospective validation is required, the objective anatomic metrics provided by this system hold promising potential to assist in preoperative assessment and surgical planning for primary acquired nasolacrimal duct obstruction treatment.